WO2021152022A1 - Système et procédé de traitement de données de mesure - Google Patents

Système et procédé de traitement de données de mesure Download PDF

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Publication number
WO2021152022A1
WO2021152022A1 PCT/EP2021/052005 EP2021052005W WO2021152022A1 WO 2021152022 A1 WO2021152022 A1 WO 2021152022A1 EP 2021052005 W EP2021052005 W EP 2021052005W WO 2021152022 A1 WO2021152022 A1 WO 2021152022A1
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WIPO (PCT)
Prior art keywords
measurement
specifiers
data
processing system
intermediary
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PCT/EP2021/052005
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English (en)
Inventor
Baher AL HAKIM
Bassel ALKHATIB
Mouhamad KAWAS
Wessam MURAI
Original Assignee
Medicus Ai Gmbh
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Publication date
Priority claimed from EP20182720.1A external-priority patent/EP3929929A1/fr
Application filed by Medicus Ai Gmbh filed Critical Medicus Ai Gmbh
Publication of WO2021152022A1 publication Critical patent/WO2021152022A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

Definitions

  • the present invention relates to the field of processing measurement data, particularly measurement data generated by bio-medical laboratories.
  • a measure the result of a quantitative measurement process, is typically stored as a number together with a unit corresponding to the dimension of the result. For example, a measurement of a length can be stored as 59 mm, 5,9 cm or 2,323 inch.
  • Measuring a height of a car it is necessary to specify under which circumstances such a weight was measured: Air pressure in the tires, load and even modifications of the vehicle may have an impact.
  • a measure of a viscosity of a fluid is typically only meaningful together with an indication of the temperature of the fluid.
  • a concentration of a substance can be measured in different tissues or body fluids.
  • this value is not meaningful without an indication of the body fluid or tissue in which it was measured.
  • the measuring method may impact a result: For example, when determining a concentration of a substance, such as cholesterol high-density lipoprotein, the measuring method may lead to different measurement values for a same sample or samples from a same user.
  • a reference or name of a generated measurement may be relevant, so as to allow processing of the values by means of a data-processing system.
  • different measurement systems for example from different laboratories, but also different machines or sensing units, may use different unit systems for same measures and may generated measures based on different standards.
  • EP1200839A1 discloses an integrated clinical laboratory software system for testing a specimen.
  • US 2011/0119309 A1 discloses a gateway enabling medical (including genetic and genomic) laboratories and health care providers (collectively “clients”) to communicate electronic messages with each other without developing and maintaining an interface for each peer.
  • W02003040697A1 discloses a method and devices for the cross-referencing of identification of object supports, for microtomised analytical samples still to be mounted thereon, with identification information for a support of a tissue sample which is not yet microtomised.
  • the conventional problem of cross-referencing is improved in a simple manner, whereby the identification information for the support is automatically generated during the very allocation in the microtome and an identification, corresponding thereto, is automatically transferred to at least one object support and that finally said object support, provided with the identification is given for the application of the microtomised tissue sample at the moment when a microtomised tissue sample must be applied to an object support.
  • a method comprises processing measurement specifiers from a plurality of sets of measurement specifiers.
  • the plurality of sets of measurement specifiers comprises at least a first set of measurement specifiers and a second set of measurement specifiers.
  • the measurement specifiers can specify measurements to be performed. For example, they can specify a variable to be sensed, such as a length of an object or a portion thereof, a weight, a concentration, a presence of a substance, organism or the like, or to a temperature.
  • At least one measurement specifier can relate to measurements that can be performed automatically.
  • At least one measurement specifier can relate to a measurement unit or a set of measurement units to be used.
  • At least one measurement specifier can relate to a sample based on which the measurement is to be performed.
  • At least one measurement specifier can relate to a measuring method by which the measurement is to be generated.
  • measuring is intended to refer to measuring in the classical sense, but for example also to chemical, bio-chemical or biologic analysis of an object, which generates information about at least one physical, chemical, biological or bio-medical feature of the object.
  • the object can for example be a sample.
  • the measuring can be direct, such as measuring a temperature by means of a sensing unit configured for sensing the temperature. It can also refer to indirectly determining data based on sensed data, for example, an acceleration can be indirectly measured by measuring a corresponding velocity and generating a derivate with respect to the time, or by an adapted sensing unit that senses a force of an object with known inertia against the accelerated object.
  • a concentration of a substance A in a mixture B is measured by determining the amount of substance A in a known or determined amount of substance B. As discussed above, this can for example be the case when measuring a concentration of cholesterol in blood of a user.
  • the method can be performed by a data-processing system.
  • the data processing device can comprise means of data processing, such as, processor units, hardware accelerators and/or microcontrollers.
  • the data processing device can comprise memory components, such as, main memory (e.g. RAM), cache memory (e.g. SRAM) and/or secondary memory (e.g. HDD, SDD).
  • the data processing device 20 can comprise busses configured to facilitate data exchange between components of the data processing device, such as, the communication between the memory components and the processing components.
  • the data processing device can comprise network interface cards that can be configured to connect the data processing device to a network, such as, to the Internet.
  • the data processing device can comprise user interfaces, such as: • at least one output user interface, such as: o screens or monitors configured to display visual data, o speakers configured to communicate audio data (e.g. playing audio data to the user),
  • • at least one input user interface such as: o a camera configured to capture visual data (e.g. capturing images and/or videos of the user, a report, the sample or the like), o a microphone configured to capture audio data (e.g. recording audio from the user), o a keyboard configured to allow the insertion of text and/or other keyboard commands (e.g. allowing the user to enter text data and/or other keyboard commands by having the user type on the keyboard) and/or o a trackpad, mouse, touchscreen, joystick.
  • a camera configured to capture visual data (e.g. capturing images and/or videos of the user, a report, the sample or the like)
  • o a microphone configured to capture audio data (e.g. recording audio from the user)
  • o a keyboard configured to allow the insertion of text and/or other keyboard commands (e.g. allowing the user to enter text data and/or other keyboard commands by having the user type on the keyboard) and/or o a trackpad, mouse, touchscreen, joy
  • the data processing device 20 can be a processing unit configured to carry out instructions of a program.
  • the data processing device 20 can be a system-on-chip comprising processing units, memory components and busses.
  • the data processing device 20 can be a personal computer, a laptop, a pocket computer, a smartphone, a tablet computer.
  • the data processing device 20 can be a server.
  • the data processing device 20 can be a processing unit or a system-on-chip that can be interfaced with a personal computer, a laptop, a pocket computer, a smartphone, a tablet computer and/or user interfaces (such as the above-mentioned user interfaces).
  • the method can comprise performing an association step.
  • the association step can comprise associating the measurement specifiers of the first set of measurement specifiers to the measurement specifiers of the second set of measurement specifiers respectively.
  • the association step can comprise associating single measurement specifiers of the first set of measurement specifiers to corresponding single measurement specifiers of the second set. That is, the association step can comprise generating associations of the specifiers of the first set and specifiers of the second set.
  • Each association can associate one specifier from the first and one from the second set. More generally, each association can relate to at most one specifier per set.
  • the association step can further comprise generating association data.
  • the association data can comprise an association portion indicating the generated associations of measurement specifiers from different sets of measurement specifiers.
  • the associations of measurement specifiers from different sets can for example associations from the first set to one or a plurality of other sets (1-n relationship), but they can also be associations of measurement specifiers from different sets to different sets (n- n relationship).
  • the plurality of sets of measurement specifiers can comprises further sets of measurement specifiers.
  • the association step can comprise associating measurement specifiers of the first set of measurement specifiers to measurement specifiers from a plurality of the other sets of measurement specifiers, respectively.
  • the association step can comprise generating the associations from the first set of measurement specifiers to the other sets of measurement specifiers. There can then be a 1-n relationship: Each specifier from the first set is associated to specifiers from the other sets, as far as the other sets comprise specifiers to which the respective specifier can be associated. However, in such a context, there can be specifiers from the other sets, that are not (yet) associated.
  • the association step can also comprise associating measurement specifiers from a plurality of the sets of measurement specifiers to measurement specifiers from the respectively other sets.
  • the association step can also comprise generating associations from specifiers from each of the plurality of sets of measurement specifiers to specifiers from the other sets.
  • sociating may also be understood as “attempting to link”. Hence, if there are measurement specifiers in one set that cannot be linked to measurement specifiers in one or more other sets, as these one or more other sets do not comprise matching counterparts, the attempting to link or to associate may still be understood as “associating”.
  • the data-processing system can comprise an association component.
  • the association component performs the association step.
  • the association component may be a software component.
  • the association component can comprise a portion of a software, or a portion of one or more software components.
  • the association component can also comprise a data- processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • Associating measurement specifiers can be associating corresponding specifiers from the different sets of measurement specifiers.
  • the association step can comprise associating said measurement specifiers by generating groups of corresponding measurement specifiers from different sets of measurement specifiers.
  • the association step can comprise creating groups of corresponding measurement specifiers, wherein the specifiers in each group may each be from a different set.
  • Corresponding measurement specifiers can comprise corresponding properties. These properties can for example relate to a type of sample or a measurement method.
  • Corresponding measurement specifiers can comprise corresponding measurable variables.
  • the corresponding measurable variables can be corresponding measurement variables.
  • the measurable variables can be variables that are to be specified by the measurement.
  • Corresponding measurement specifiers can comprise corresponding bio-medical properties. They can for example relate to same or corresponding bio-medical variables, such as a count of white blood cells.
  • Corresponding measurement specifiers can comprise corresponding biomarkers.
  • measurement specifiers comprising corresponding biomarkers, properties, measurable values and/or bio-medical properties
  • this can refer to the measurements which the measurement specifiers respectively specify, as the person skilled in the art will easily understand.
  • Measurement specifiers from at least one group of corresponding measurement specifiers comprise different measurement units. That is, these measurement specifiers may specify measurements which generate results having a same dimension, such as a length, but different measurement units, such as cm and inch. However, these measurement specifiers may also specify corresponding measurements, which generate results in different dimensions, such as a concentration, which can be for example have the dimension n/V, m/V or V/V.
  • the method may comprise assigning to some or all of the measurement specifiers of the sets of measurement specifiers an indication of a corresponding intermediary specifier of a set of intermediary specifiers, respectively.
  • the indication can for example be a reference, a pointer, or a constant value indicating the corresponding intermediary specifier, such as a name or an ID.
  • an indication of an intermediary specifier can be assigned to a plurality of measurement specifiers from the plurality of sets.
  • the relation of the measurement specifiers to the intermediary specifiers can be a n-to-l-relation.
  • the association data can comprise an intermediary portion comprising the assignments of the indications of the intermediary specifiers to the measurement specifiers.
  • the association step can comprise associating the measurement specifiers from the sets of measurement specifiers by the assigned indicators of the intermediary specifiers.
  • the association step can comprise assigning measurement specifiers to each other, to which indicators of the same intermediary specifier are assigned.
  • the association step can comprise generating the association portion of the association data based on the assigned indicators from the intermediary portion.
  • the method can comprise performing a pre-processing step.
  • the data-processing system can comprise a pre-processing component.
  • the pre processing component can perform the pre-processing step.
  • the pre-processing component may be a software component.
  • the pre-processing component can comprise a portion of a software, or a portion of one or more software components.
  • the pre-processing component can also comprise a data-processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • the pre-processing step can comprise pre-processing specifiers from the sets of measurement specifiers.
  • the pre-processing step can also comprise pre-processing specifiers from the set of intermediary specifiers.
  • specifiers When in the following, reference is made to pre-processing one or more specifiers, this can relate to the specifiers as a whole. However, it can also refer to corresponding elements of the specifiers, such as reference elements of the specifiers. These reference elements can be identifiers, such as names or identification numbers.
  • the indication of an intermediary specifier, as well as an indication of a measurement specifier, can comprise the respective reference element.
  • the pre-processing step can also comprise pre-processing specifiers from at least one of (a) the sets of measurement specifiers and (b) the set of intermediary specifiers.
  • Pre-processing a specifier can comprises applying a removing criterion to the specifier and removing a portion of the specifier accordingly.
  • the removing criterion can indicate removal of certain signs.
  • the removing criterion can also indicate for one or more specifiers to not remove anything.
  • An optional advantage can be that parts of the specifier(s) which are unspecific, erroneous or irrelevant do not hinder the further processing of the specifier(s).
  • Pre-processing a specifier can comprise generating a hash-value for the specifier.
  • Generating a hash-value for the specifier can be performed by means of a hash function, which can be cryptographic, but which does not need to be cryptographic.
  • a hash function can be cryptographic, but which does not need to be cryptographic.
  • an length or amount of characters of a specifier can also be a hash-function.
  • Another example can be a sum of parts of an element of the specifier, such as a sum of ASCII-values of characters of a reference element of the specifier, as discussed above.
  • Generating the hash-value for the specifiers can be optionally advantageous as it allows to easily detect identical terms, since their hash-value can be identical, and comparing hash values of specifiers may be less computing-time intensive than comparing the specifiers (or their reference elements).
  • some hash functions such as the sum of parts of an element of the specifier, such as the reference element, generate a same result for two elements that are identical apart from an exchanged order. This can be a resource-efficient way to estimate specifiers or elements thereof that are identical apart from an interchange, compared to a comparison algorithm that exactly determines whether two specifiers or elements are identical apart from an interchange.
  • Pre-processing a specifier can comprise generating a plurality of different hash-values for the specifier.
  • a second function may yield different outputs.
  • calculating two hashes by means of fast hash functions may still be more resource efficient than calculating one hash by mean of a complex hash function.
  • the pre-processing step can comprise pre-processing the measurement specifiers, and the method can comprise loading and/or receiving a result of pre-processing the intermediary specifiers.
  • Loading the result of pre-processing can be loading this result from a data storage.
  • Receiving can be receiving the result from another data-processing system, such as a database server.
  • An optional advantage of loading and/or receiving the result of pre-processing the intermediary specifiers can be that the intermediary specifiers remain mostly constant, in contrast to the measurement specifiers, which may be specific to each execution of the method. Hence, loading and/or receiving the result of pre-processing the intermediary specifiers may save calculation time, when the method is executed multiple times with same or similar sets of intermediary specifiers.
  • the method can comprise a subset-selection step.
  • the pre-processing component can perform the subset-selection step.
  • the subset-selection step can comprise for each of a plurality of measurement specifiers to be associated, selecting a subset of the set of intermediary specifiers based on a similarity of the respective measurement specifier and the intermediary specifiers.
  • the subset-selection step can comprise selecting for each measurement specifier a subset of the intermediary specifiers, which comprises intermediary specifiers whose similarity to the respective measurement specifier exceeds a certain threshold.
  • the "similarity" can for example also refer to or comprise a similarity of elements of the specifiers, such as the reference element of each specifier.
  • the subset may be empty, particularly if there is no intermediary specifier whose similarity to the measurement specifier exceeds the threshold.
  • the plurality of measurement specifiers to be associated can be a plurality of measurement specifiers to be associated with corresponding measurement specifiers, as discussed above.
  • the subset-selection step can comprise determining the similarity by means of a similarity measure, wherein the similarity measure is based at least on a result of the pre-processing of the respective measurement specifier and the intermediary specifiers.
  • the similarity can be a similarity of the hash values generated by the pre-processing function.
  • the subset can be an estimation, comprising an intermediary specifier that corresponds to the respective measurement specifier.
  • following comparison which may be more time consuming, can then be limited to this subset, and hence consume less computing time.
  • the similarity measure can be based at least on the hash-values generated for the specifiers.
  • the similarity measure can comprise an absolute value of a distance between the hash value(s) of the measurement specifiers and the intermediary specifiers.
  • the absolute value of the distance can be the mathematical absolute value of the distance which is denoted as
  • the distance can be a difference, in the scalar case. In case of a plurality of hash values or non-scalar hash values, other distances can be used, such as an Euclidian distance or a Manhattan distance.
  • Selecting the subset of the set of intermediary specifiers can comprise selecting intermediary specifiers for which the similarity measure exceeds a subset-selection threshold.
  • the above-discussed threshold for the similarity can be the subset-selection threshold.
  • the subset-selection threshold can be constant.
  • the subset-selection threshold can also be variable. For example, for each measurement specifier, the subset-selection threshold can have a start value dl. If the corresponding subset is empty, the threshold can be successively lowered to a value d2 and optionally d3 a.s.o., until either the subset is not empty anymore, or the threshold reaches a minimum value dmin. In the latter case, the subset may remain empty.
  • This sliding threshold can for example be optionally advantageous in cases where a quantity of errors in the input data is not known and the threshold is lowered, if the subsets found with the prior threshold are empty or sparse, and the threshold is raised, if the subsets found comprise too many intermediary specifiers.
  • Selecting the subset of t/he set of intermediary specifiers can comprise selecting only intermediary specifiers for which the similarity measure exceeds the subset-selection threshold.
  • the subset-selection step can be optionally advantageous, as it can provide an estimation of corresponding specifiers with less calculation efforts than by comparing a specifier of one set to each specifier of another set, until they match.
  • the pre-processing step can be optionally advantageous, as it provides a base for the subset-selection step.
  • the method can comprise performing a matching step.
  • the data-processing system can comprise a matching component.
  • the matching component can perform the matching step.
  • the matching component may be a software component.
  • the matching component can comprise a portion of a software, or a portion of one or more software components.
  • the matching component can also comprise a data-processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • the matching step can comprise matching at least some of the measurement specifiers to corresponding intermediary specifiers.
  • Matching is intended to refer to a process of matching and generating an association of the matched specifiers. However, in some cases, matching may not lead to a generated association for some measurement specifiers, for example if there is no corresponding intermediary specifier in the set of intermediary specifiers or if the matching is not possible for other reasons. For example, the specifiers can differ in a way that was unforeseen or unforeseeable when the method was implemented.
  • the matching step can comprise matching at least some of the measurement specifiers to corresponding intermediary specifiers by means of a comparison criterion.
  • Matching the at least some of the measurement specifiers to corresponding intermediary specifiers can be based at least one the subsets of the intermediary specifiers respectively selected for the measurement specifiers.
  • for matching step can comprise for each of a plurality of measurement specifiers attempting to match the measurement specifier only to one of the intermediary specifiers from the respective subset, or to match said measurement specifier first to one the intermediary specifiers from the respective subset and only attempt to match the measurement specifier to other intermediary specifiers if this attempt fails.
  • the matching step can further comprise assigning at least the indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step can comprise matching the measurement specifiers to the corresponding intermediary specifiers.
  • the matching step can also comprise assigning at least an indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step can comprise applying the comparison criterion to at least one pair of a measurement specifier and an intermediary specifier.
  • this can comprise or mean comparing or applying the comparison criterion to corresponding elements of the specifiers, such as the reference elements of the specifiers, as discussed in the context of the pre-processing step and the subset-selection step.
  • Each pair can also comprise a measurement specifier and an intermediary specifier from the subset of intermediary specifiers selected for said measurement specifier (or their reference elements).
  • the comparison can be limited to the intermediary specifiers selected by the subset-selection step. As discussed above, this can be optionally advantageous, as the generation of the subset of intermediary specifiers and the subsequent comparison of the respective measurement specifier to this subset may require less computation time than a comparison of the measurement specifier to each intermediary specifier (until the measurement specifier is matched).
  • the method can comprise assigning the measurement specifiers to the respective intermediary specifiers to which the measurement specifiers where matched.
  • the method can comprise associating the measurement specifiers from the sets of measurement specifiers, which measurement specifiers were matched to same intermediary specifiers respectively.
  • the method can comprise associating measurement specifiers from different sets that were matched to a respectively same intermediary specifier.
  • the method, particularly the association step can further comprise associating the measurement specifiers that were matched to intermediary specifiers based on this principle.
  • the request data can request a user to perform an action, for example to provide or input data.
  • the request data can also request a server system to perform an action, for example to send data.
  • the data-processing system can generate the request data.
  • the request data can comprise at least an indication of at least one measurement specifier.
  • the indication can comprise an element of the measurement specifier, such as the reference element.
  • the matching step can comprise generating request data for at least one measurement specifier for which no yielded matching probability exceeds the matching threshold.
  • the matching step can comprise generating a portion of the request data if, for at least one measurement specifier, the generated matching probability for all intermediary specifiers is below the matching threshold.
  • Generating the request data in the above-mentioned cases can be optionally advantageous, because it can limit a necessary interaction of the user with the system, and it can allow however matching all specifiers that can be matched by a human. Hence, matching can be performed faster and with less user-interaction.
  • the method can comprise sending the request data.
  • the output-node can comprise an output interface.
  • the output-node can further comprise an output-data processing system.
  • the output-data processing system can comprise elements of a data-processing system analogously to the data-processing system discussed above.
  • the data-processing system can comprise a data-transmission component.
  • the data- transmission component can for example comprise a network interface controller.
  • the network interface controller can be adapted for connecting the data-processing system to a network via technologies well-known in the art, such as ethernet or Wifi.
  • the data-transmission component can send the request data.
  • the data-transmission component can receive the input data.
  • the input data can comprise at least one or a plurality of input pair(s).
  • Each input pair can comprise a measurement specifier and a corresponding intermediate specifier.
  • some of the input pairs can each comprise an association of at least one measurement specifier and a corresponding intermediate specifier.
  • some of the input pairs can also each comprise an association of a plurality of measurement specifiers and a corresponding intermediate specifier.
  • An optional advantage can be that thus, the method can send request data for measurement specifiers that the method cannot successfully match, and receive the corresponding matching, so that more measurement specifiers can be matched. Hence, an overall flexibility of a system or method using the associations of the measurement specifiers can be increased.
  • the matching step can comprise matching at least one or at least some of the measurement specifiers to the corresponding intermediary specifier(s) based on the input data, optionally as discussed above.
  • the method can comprise receiving a part of the input data after sending the request data.
  • Each intermediary specifier can comprise a reference.
  • the reference can be a reference element as discussed above.
  • At least one or a plurality of intermediary specifier(s) can further comprise at least one or a plurality of alternative reference(s).
  • the reference element can comprise the alternative reference(s) as well as the reference.
  • the reference element can be the alternative reference and the reference.
  • the method can comprise generating at least a portion of the alternative reference(s) of the at least one or the plurality of intermediary specifier(s).
  • the method can comprise generating the alternative reference(s) of the at least one or the plurality of intermediary specifier(s) based at least on the pair(s) of measurement specifiers and corresponding intermediate specifiers from the matching-input data.
  • the method can comprise receiving at least a portion of the alternative references from a second data-processing system.
  • the data-transmission component can receive at least the portion of the alternative references from the second data-processing system.
  • the method can comprise storing the alternative references.
  • the method can also comprise storing the reference elements.
  • the data-processing system can comprise a data-storage component.
  • the data-storage component can comprise persistent memory, such as a hard drive or a flash memory unit.
  • the second data-processing system can access a database.
  • Said database can comprise a plurality of intermediate specifiers.
  • Said database may particularly comprise the reference elements of the intermediate specifiers or at least a part thereof.
  • the method can comprises generating at least some of the alternative reference(s) in at least one of the matching step, the subset-selection step, and both of them.
  • the method can further comprise using the alternative reference(s) in a remainder of the respective step(s) or the method.
  • the method can comprise generating at least some of the alternative reference(s) before finishing the subset-selection step for at least one set of measurement specifiers.
  • the method can comprise generating at least some of the alternative reference(s) before for at least one subset of measurement specifiers, the corresponding subsets of intermediary specifiers are selected.
  • the verification component can perform the verifying step.
  • the verification component may be a software component.
  • the verification component can comprise a portion of a software, or a portion of one or more software components.
  • the verification component can also comprise a data- processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • Verifying said compatibility can comprise verifying a compatibility of a measurement unit of the respective measurement specifier to a group of measurement units associated with the respective intermediary specifier.
  • the group of measurement units can comprise a plurality of units for a same measure which units indicate a same dimension, such as °C, K and °F for a temperature, or m, mm, cm, dm, inch and ft.
  • the group of measurement units can also comprise units which indicate different dimensions, e.g. for a concentration, as discussed above.
  • Verifying said compatibility can comprise verifying a compatibility of an attribute of the respective measurement specifier to a group of attributes associated with the respective intermediary specifier.
  • the method can comprise generating request data for the measurement specifier.
  • An optional advantage can be that in case that errors in the matching can be reduced an again, the fail safety of the method can be increased.
  • the generated request data can further comprise at least an indication of the respective intermediary specifier.
  • the comparison criterion can comprise a matching-similarity measure.
  • the matching-similarity measure may be different from the similarity measure used in the subset-selection step.
  • Applying the comparison criterion can comprises processing a result of the verifying step for the measurement specifier and the intermediary specifier.
  • the set of intermediary specifiers can correspond to an encoding B.
  • the encoding B can further be a standard encoding. That is, the encoding B can be an encoding used for a plurality, particularly a multitude of sets of specifiers. Preferably, the encoding is optimized for interoperability of systems. Examples of a standard encoding for measurements can for example be an encoding according to the LOINC-standard or the SNOMED-standard.
  • the encoding B can also comprise a standard encoding.
  • Each of the sets of measurement specifiers can be associated with at least one measurement-data processing system.
  • the measurement-data processing system can for example be a laboratory information system.
  • At least some of the measurement specifiers can each be associated with a respective attribute or a group of attributes, as discussed above for the intermediate specifiers.
  • At least some of the measurement specifiers can comprise attributes relating to a measurement procedure for generating measurement values specified by the respective measurement specifier.
  • At least some of the measurement specifiers can comprise a measurement unit or an indication thereof.
  • the method can comprise receiving at least one or a plurality of set(s) of measurement results.
  • Each set of measurement results can comprise at least one or a plurality of data points.
  • the method can comprise a modification step.
  • the data-processing system can comprise a modification component.
  • the modification component may be a software component.
  • the modification component can comprise a portion of a software, or a portion of one or more software components.
  • the modification component can also comprise a data- processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • the modification component can perform the modification step.
  • the modification step can comprise generating modified set(s) of measurement results so as to be each according to a respective target-set of the sets of measurement specifiers.
  • the target-set can be different from the origin-set.
  • a receiver may use data-processing systems adapted for a first set of measurement specifiers, and a measurement-data processing system may be adapted for another set of measurement specifiers.
  • Generating the modified set(s) of measurement results can based on the association data.
  • the corresponding measurement specifier of the target-set can be found.
  • a reference element can be replaced.
  • Generating the modified set(s) of measurement results can comprise generating modified data points of each of the set(s) of measurement results.
  • the modified data points can be according to the respective target-set of measurement specifiers.
  • Generating modified data points can comprise generating new data points based on the initial ones, and/or modifying the initial data points.
  • Generating the modified data points can further comprise converting at least one of the data points to a measurement unit of the corresponding measurement specifier of the target-set.
  • the data-processing system can receive the set(s) of measurement results.
  • the data-transmission component can receive the set(s) measurement results.
  • the method can comprise a measuring step.
  • the measuring step can comprise generating the set(s) of measurement results by the measurement-data processing system(s).
  • Generating the set(s) of measurement results can for example comprise processing or agglomerating the measurement results. Generating the set(s) of measurement results can also comprise combining received data or performing further processing steps, such as storing generated data or retrieving stored data, for example comparison data.
  • the method can comprise transmitting measurement data from each set of measurement equipment to the corresponding measurement-data processing system.
  • the transmission can be performed automatically.
  • the transmission can also be performed by an agent.
  • a plurality of measurement results from a same measurement-data processing system can comprise the same origin-set.
  • All measurement results from same measurement-data processing systems can comprise the same origin-set.
  • a measurement-data processing system can be setup to generate the measurement according to one set of measurement specifiers, which can then be the origin-set.
  • At least some measurement results from different measurement-data processing systems can comprise different origin-sets. This can for example be the case when the measurement-data processing system where setup differently.
  • the sets of measurement results can comprise medical measurement results. That is, the sets of measurement results can comprise results of measurements relating to variables that are medically relevant, such as a white blood cell count, a concentration of cholesterol HDL or the like. The measurements can also be used for a generation of a medical diagnosis.
  • Each set of measurement equipment can comprise bio-medical measurement equipment. That is, each set of measurement equipment can be configured for measuring bio-medical data.
  • the method can comprise generating the measurement data by means of the set(s) of measurement equipment.
  • the method can comprise transmitting the modified set(s) of measurement results.
  • the method can comprise transmitting the modified set(s) of measurement results to different target-data processing systems.
  • the method can comprise receiving at least an indication of the target-data processing system for each set of measurement results.
  • the method can comprise determining the target-set for each set of measurement results based on the target-data processing system for the set of measurement results.
  • the method can comprise outputting the at least one of the modified set(s) of measurement results by means of the corresponding target-data processing system.
  • the target-data processing system can comprise at least one output device, such as a screen or a speaker, by means of which the target-data processing system can output the data.
  • the data-processing system can transmit the modified set(s) of measurement results.
  • the data-processing system can transmit the modified set(s) of measurement results to the corresponding target-data processing system(s).
  • the data-transmission component can transmit the modified set(s) of measurement results.
  • the method can comprise processing instruction data.
  • the instruction data can comprise at least one or a plurality of measurement instruction set(s).
  • the measurement instruction set(s) can comprise instructions instructing the measurement-data processing system to trigger corresponding measurements.
  • the data-processing system receives the measurement instruction set(s) and/or the instruction data from the target-data processing system(s).
  • the data-processing system can transmit the measurement instruction set(s) to the at least one or the plurality of measurement-data processing system(s).
  • the measuring step can comprise generating the set(s) of measurement result(s) based on the measurement instruction set(s) by the measurement-data processing system(s).
  • the measurement-data processing systems can perform the steps discussed above during the measuring step.
  • Each measurement instruction set can comprise sample data, wherein the sample data of each instruction set comprise at least one or a plurality of sample identifier(s) for a sample(s) to be analysed.
  • the measuring step can comprise for each measurement instruction set, generating the respective set of measurement result(s) by processing the sample(s) corresponding to the sample identifier(s) of the measurement instruction set.
  • the data-processing system can receive the measurement instruction set(s) from the target-data processing system(s).
  • the measurement instruction specifiers of the measurement instruction set(s) can be initially according to the respective target-set. For example, when a target-data processing system, such as a data-processing at an MDs office, or in a department for quality control, generates or processes the instruction set, the measurement instruction set may correspond to a set of measurement specifiers that the corresponding target-data processing system uses.
  • the measurement instruction specifiers of the measurement instruction set(s) that the data-processing system transmits to the measurement-data processing system(s) can be according to the respective origin-set.
  • the data-processing system can transmit each of at least some or all of the measurement instruction set(s) to the measurement-data processing systems in a form according to the origin-set of the respective measurement-data processing system.
  • the modification step can comprise modifying at least some of the measurement instruction specifiers by the data-processing system so as to be according to the respective origin-set.
  • An optional advantage can be that the method enables a measurement-data processing system to process measurement instruction sets that were generated using measurement specifiers that are not from the origin-set of the respective measurement-data processing system.
  • this can optionally advantageously increase an interoperability of the measurement-data processing systems with respect to different target-data processing systems and a flexibility of an overall system comprising the target-data processing systems and the measurement-data processing systems.
  • the modification step can comprise generating modified measurement instruction specifiers of measurement instruction set(s) whose respective origin- set and target-set are different.
  • the modification step can comprise generating modified measurement instruction specifiers for measurement instruction sets whose target-data processing systems use target-sets different from the set of measurement specifiers that the respective measurement-data processing systems use.
  • the modification step can comprise generating the modified measurement instruction specifiers according to the set(s) of measurement specifiers that the respective measurement-data processing system(s) use, which measurement-data processing system(s) generate the corresponding measurement results in the measuring step.
  • Generating the modified measurement instruction specifiers can be based on the association data.
  • Each of the at least one or the plurality of measurement results can comprise a target ID.
  • the measurement instruction set(s) can comprise a target ID.
  • the respective target-data processing system can be a target-data processing system that generated the measurement instruction set to which the measurement result is according.
  • the respective target-data processing system can also be a target-data processing system that receives the measurement result to be generated.
  • Each target ID can further comprise an indication of the target-set.
  • Each of the set(s) of measurement results can comprise an origin ID.
  • each of the measurement instruction set(s) can comprise a origin ID.
  • Each origin ID can comprise an indication of the respective measurement data-processing system.
  • Each origin ID can further comprise an indication of the origin set.
  • Generating the modified measurement instruction specifiers can further be based on the target ID and the origin ID.
  • the data-processing system can comprise the structural and function features disclosed in the context of the method.
  • the pre-processing component can further be configured for performing a subset-selection step.
  • the data-processing system can further comprise a matching component.
  • the matching component can be configured for performing a matching step.
  • the data-processing system can comprise a verification component.
  • the verification component can be configured for performing a verifying step.
  • the data-processing system can comprise a modification component.
  • the modification component can be configured for performing a modification step.
  • Each of the association component, the pre-processing component, the matching component, the verification component and the modification component may be a software component.
  • Each of the components can comprise a portion of a software, or a portion of one or more software components.
  • Each of the components can also comprise a data- processing unit configured for this purpose, such as a microcontroller with an adapted software, or an FPGA.
  • the data-processing system can comprise a data-storage component.
  • the data-storage component can comprise persistent memory, such as flash memory or a hard disc.
  • the data-processing system can further comprise a data-transmission component.
  • the data-transmission component can for example comprise a network interface controller.
  • the network interface controller can be adapted for connecting the data-processing system to a network via technologies well-known in the art, such as ethernet or Wifi.
  • the system may further comprise an output node.
  • the output node may be configured for outputting data.
  • the system may further comprise a second data-processing system.
  • the system can comprise at least one or a plurality of target-data processing system(s).
  • the association step can comprise associating the measurement specifiers of the first set of measurement specifiers to the measurement specifiers of the second set of measurement specifiers respectively.
  • the association step can be according to the disclosure relating to the above-discussed method.
  • the association step can further comprise generating association data.
  • the association data can comprise an association portion.
  • the association step can also comprise associating measurement specifiers from each of the sets of measurement specifiers to measurement specifiers from the respectively other sets.
  • the measurement specifiers in each group may be from different sets of measurement specifiers. Note also the clarification in the context of the method.
  • Corresponding measurement specifiers can comprise corresponding measurable variables.
  • Corresponding measurement specifiers can comprise corresponding bio-medical properties.
  • Corresponding measurement specifiers can comprise corresponding biomarkers.
  • Measurement specifiers from at least one group of corresponding measurement specifiers can comprise different measurement units.
  • these measurement specifiers may specify measurements which generate results having a same dimension. However, these measurement specifiers may also specify corresponding measurements, which generate results in different dimensions.
  • the data-processing system can be configured for assigning to some or all of the measurement specifiers of the sets of measurement specifiers an indication of a corresponding intermediary specifier of a set of intermediary specifiers, respectively.
  • the indication of the corresponding intermediary specifier can be the intermediary specifier.
  • the indication of the corresponding intermediary specifier can also be a reference element of the intermediary specifier.
  • an intermediary specifier can be assigned to a plurality of measurement specifiers from the plurality of sets.
  • the relation of the measurement specifiers to the intermediary specifiers can be a n-to-l-relation.
  • the association data can comprise an intermediary portion comprising the assignments of the indications of the intermediary specifiers to the measurement specifiers.
  • the association step can comprise associating the measurement specifiers from the sets of measurement specifiers by the assigned indicators of the intermediary specifiers.
  • the association step can comprise generating the association portion of the association data based on the assigned indicators from the intermediary portion.
  • the pre-processing step can comprise pre-processing specifiers from the sets of measurement specifiers.
  • the pre-processing step can further comprise pre-processing specifiers from the set of intermediary specifiers.
  • Pre-processing a specifier can comprise applying a removing criterion to the specifier and removing a portion of the specifier accordingly.
  • the removing criterion can indicate removal of certain signs.
  • the removing criterion can also indicate for one or more specifiers to not remove anything.
  • Pre-processing a specifier can comprise generating a hash-value for the specifier.
  • Pre-processing a specifier can comprise generating a plurality of different hash-values for the specifier.
  • the pre-processing step can comprise pre-processing the measurement specifiers.
  • the data-processing system can be configured for loading and/or receiving a result of pre processing the intermediary specifiers.
  • the pre-processing step can comprise the subset-selection step.
  • the subset-selection step can comprise for each of a plurality of measurement specifiers to be associated, selecting a subset of the set of intermediary specifiers based on a similarity of the respective measurement specifier and the intermediary specifiers. As discussed above, said subset may be empty.
  • the plurality of measurement specifiers to be associated can be a plurality of measurement specifiers to be associated to corresponding measurement specifiers.
  • the subset-selection step can comprise determining the similarity by means of a similarity measure.
  • the similarity measure can be based at least on a result of the pre-processing of the respective measurement specifier and the intermediary specifiers.
  • the similarity measure can be based at least on the hash-values generated for the specifiers.
  • the similarity measure can comprise an absolute value of a distance between the hash value(s) of the measurement specifiers and the intermediary specifiers.
  • Selecting the subset of the set of intermediary specifiers can comprise selecting intermediary specifiers for which the similarity measure exceeds a subset-selection threshold.
  • Selecting the subset of the set of intermediary specifiers can comprise selecting only intermediary specifiers for which the similarity measure exceeds the subset-selection threshold.
  • the matching step can comprise matching at least some of the measurement specifiers to corresponding intermediary specifiers.
  • the matching step can comprise matching at least some of the measurement specifiers to corresponding intermediary specifiers by means of a comparison criterion.
  • Matching the at least some of the measurement specifiers to corresponding intermediary specifiers can be based at least one the subsets of the intermediary specifiers respectively selected for the measurement specifiers.
  • the matching step can further comprise assigning at least the indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step can comprise matching the measurement specifiers to the corresponding intermediary specifiers.
  • the matching step can further comprise assigning at least an indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step can comprise applying the comparison criterion to at least one pair of a measurement specifier and an intermediary specifier.
  • the matching step can comprise applying the comparison criterion to a plurality of pairs.
  • Each pair can comprise a measurement specifier and an intermediary specifier.
  • the matching step can comprise applying the comparison criterion to the plurality of pairs.
  • Each pair can comprise a measurement specifier and an intermediary specifier from the subset of intermediary specifiers selected for said measurement specifier.
  • the matching step can comprise matching each measurement specifier to the intermediary specifier for which the comparison criterion yields and/or estimates a maximum matching probability.
  • the matching step may comprise matching each measurement specifier only to an intermediary specifier, if, furthermore, a result of the comparison criterion exceeds a matching threshold.
  • the data-processing system can be configured for associating the corresponding specifiers from the sets of measurement specifiers based on the intermediary specifiers to which the measurement specifiers were matched.
  • the data-processing system can be configured for performing at least a part of the association step based on a result of the matching step.
  • the association component can be configured for performing the part of the association step based on the result of the matching step.
  • the data-processing system preferably the association component, can be configured for associating the measurement specifiers from the sets of measurement specifiers which measurement specifiers were matched to same intermediary specifiers respectively.
  • the data-processing system can be configured for generating request data.
  • the request data can comprise at least an indication of at least one measurement specifier.
  • the matching step can comprise generating request data for at least one measurement specifier for which no yielded or estimated matching probability exceeds the matching threshold.
  • the matching step can comprise generating request data for at least one measurement specifier for which an application of the comparison criterion does not yield a corresponding intermediary specifier in the matching step. For more details, see the corresponding details discussed in the context of the method.
  • the data-processing system can be configured for sending the request data.
  • the data-processing system can be configured for sending the request data to the output- node.
  • the output-node can comprise an output interface, such as a screen for displaying data or a speaker to play audio data.
  • the output-node can be configured for outputting data.
  • the output-node can be configured for outputting request data.
  • the output- node can be configured for outputting the request data or at least a part of the request data.
  • the data-transmission component can be configured for sending the request data.
  • the data-processing system can be configured for receiving input data.
  • the data-transmission component can be configured for receiving the input data.
  • the input data can comprise at least one or a plurality of input pair(s). Each input pair can comprise a measurement specifier and a corresponding intermediate specifier.
  • the input pair(s) can comprise the at least one measurement specifier corresponding to the at least one indication which the request data comprise.
  • the matching step can comprise matching at least one or at least some of the measurement specifiers to the corresponding intermediary specifier(s) based on the matching-input data.
  • the data-processing system and/or the data-transmission component can be configured for receiving the matching-input data after sending the request data.
  • Each intermediary specifier can comprise a reference.
  • At least one or a plurality of intermediary specifier(s) can further comprise at least one or a plurality of alternative reference(s).
  • Pre-processing the intermediary specifiers can be pre-processing at least one of the reference, and the alternative reference(s) of the intermediary specifiers.
  • the data-processing system can be configured for generating at least a portion of the alternative reference(s) of the at least one or the plurality of intermediary specifier(s).
  • the data-processing system can further be configured for generating the alternative reference(s) of the at least one or the plurality of intermediary specifier(s) based at least on the pair(s) of measurement specifiers and corresponding intermediate specifiers from the matching-input data.
  • the data-processing system can be configured for receiving at least a portion of the alternative references from the second data-processing system.
  • the data-transmission component can be configured for receiving at least the portion of the alternative references from the second data-processing system.
  • the data-processing system can be configured for storing the alternative references.
  • the data-storage component can comprise persistent memory, such as a hard drive or a flash memory unit.
  • the data-storage component can be configured for storing the alternative references.
  • the system can be configured for sending a part of the generated alternative references to the second data-processing system.
  • the system can also be configured for sending the generated alternative references to the third data-processing system.
  • the second data-processing system can be configured for accessing a database.
  • the database can comprise a plurality of the intermediate specifiers, that is several intermediate specifiers.
  • the matching step, the subset-selection step, or both of them can comprise generating at least some of the alternative reference(s).
  • the data-processing system can be configured for using the alternative reference(s) in a subsequent operation. That is, the data- processing system can be configured for using the alternative references generated in at least one of the matching step and the subset-selection step for following steps of the method. This can be optionally advantageous, as the respective alternative references do not need to be generated again in the subsequent part of the method.
  • the matching component, the pre-processing component, or both of them can be configured for generating at least some of the alternative reference(s).
  • the data-processing system can be configured for generating at least some of the alternative reference(s) before matching measurement specifiers from at least one set of measurement specifiers to the corresponding intermediary specifiers.
  • the data-processing system can be configured for generating at least some of the alternative reference(s) before matching a "last" set of measurement specifiers to the intermediary specifiers.
  • an optional advantage can be, that in this case, the alternative references can be used by the data-processing system at least for matching said last set of measurement specifiers to the intermediary specifiers, and that thus, at least one of less computing time, less requests to the user or less requests to the second data-processing system may be necessary. In other words, this can optionally advantageously at least reduce a number of alternative references that are redundantly generated.
  • the matching component and/or the pre-processing component can be configured for generating at least some of the alternative reference(s) before matching measurement specifiers from at least one set of measurement specifiers to the corresponding intermediary specifiers, as discussed above.
  • the data-processing system can be configured for generating at least some of the alternative reference(s) before finishing the subset-selection step for at least one set of measurement specifiers.
  • the data-processing system can be configured for generating the alterative references before the subset-selection step is finished for all sets of measurement specifiers.
  • the matching step can comprise the verifying step.
  • the matching component can comprise the verification component.
  • the verifying step can comprise verifying a compatibility for each of a plurality of the measurement specifiers to the respective intermediary specifier(s).
  • Verifying said compatibility can comprise verifying a compatibility of a measurement unit of the measurement specifier to a group of measurement units associated with the respective intermediary specifier(s).
  • said group of measurement units can comprise measurement units corresponding to the respective intermediary specifier, wherein these measurement units can correspond to a same or different dimensions.
  • Verifying said compatibility can comprise verifying a compatibility of an attribute of the respective measurement specifier to a group of attributes associated with the respective intermediary specifier.
  • the data-processing system can be configured for generating request data for a measurement specifier at least if the verifying step comes to a negative result for said measurement specifier and an intermediary specifier.
  • the generated request data can further comprise at least an indication of the respective intermediary specifier.
  • the comparison criterion can comprise a matching-similarity measure.
  • the matching-similarity measure may be different from the similarity measure in the pre-processing step.
  • the comparison criterion can comprise a comparison by a phonetic algorithm, as discussed above.
  • Applying the comparison criterion can comprise processing a result of the verifying step for the measurement specifier and the intermediary specifier.
  • the set of intermediary specifiers can be configured to correspond to an encoding B, as discussed above
  • At least some intermediary specifiers can be associated with a respective group of attributes.
  • At least a portion of the attributes can relate to a measurement procedure for generating measurement values specified by the respective intermediate specifier.
  • the measurement procedure can be as discussed above.
  • Each of the sets of measurement specifiers can be associated with at least one of the measurement-data processing system(s).
  • At least some of the measurement specifiers can each be associated with a respective attribute or a group of attributes.
  • At least some of the measurement specifiers can comprise attributes relating to a measurement procedure for generating measurement values specified by the respective measurement specifier.
  • At least some of the measurement specifiers can comprise a measurement unit or an indication thereof.
  • the data-processing system can be configured for receiving at least one or a plurality of set(s) of measurement results.
  • Each set of measurement results can comprise at least one or a plurality of data points.
  • Each data point can comprise at least one value.
  • Each data point can be according to a measurement specifier.
  • Each set of measurement results can initially be according to the respective origin-set of the sets measurement specifiers.
  • the modification step can comprise generating modified set(s) of measurement results so as to be each according to a respective target-set of the sets of measurement specifiers.
  • the target-set can be different from the origin-set.
  • Generating the modified set(s) of measurement results can be based on the association data.
  • Generating the modified set(s) of measurement results can comprise generating modified data points of each of the set(s) of measurement results.
  • the modified data points can be according to the respective target-set of measurement specifiers.
  • generating the modified set(s) of measurement results can comprise generating modified data for of each of the set(s) of measurement results so that the modified data points are according to the respective target-set of measurement specifiers after the modification.
  • the modification component can be configured for this modification.
  • Generating the modified data points further can comprise converting at least one of the data points to a measurement unit of the corresponding measurement specifier of the target-set.
  • the data-transmission component can be configured for receiving the set(s) measurement results.
  • the data-processing system can be configured for receiving the set(s) of measurement results from the measurement-data processing system(s).
  • the data-transmission component can be configured for receiving the set(s) of measurement results from the measurement-data processing system(s).
  • the measurement-data processing system(s) can be configured for generating the set(s) of measurement results.
  • the measurement-data processing system(s) can be configured for processing measurement data, agglomerating measurement data, combining measurement data, and/or performing further processing steps.
  • the measurement data-processing system(s) can be configured for receiving measurement data from the respective set of measurement equipment.
  • a plurality of measurement results from a same measurement-data processing system can comprise the same origin-set.
  • All measurement results from same measurement-data processing systems can comprise the same origin-set.
  • each measurement-data processing system can use a fixed or constant origin-set.
  • At least some measurement results from different measurement-data processing systems can comprise different origin-sets.
  • the system comprises measurement- data processing systems of which at least two are configured to use different origin sets.
  • the sets of measurement results can comprise medical measurement results.
  • Each set of measurement equipment can comprise bio-medical measurement equipment.
  • Bio-medical measurement equipment can be as discussed above. Particularly, it can be configured for performing medical, biological or bio-medical measurements.
  • Each set of measurement equipment can be configured for generating a part of the measurement data.
  • the data-processing system can be configured for transmitting the modified set(s) of measurement results.
  • the data-processing system can be configured for transmitting the modified set(s) of measurement results to the target-data processing system(s).
  • the data-transmission component can be configured for transmitting the modified set(s) of measurement results to the target-data processing system(s).
  • the data-processing system can be configured for transmitting the modified set(s) of measurement results to different target-data processing systems.
  • the data-transmission component can be configured for transmitting the modified set(s) of measurement results to different target-data processing systems.
  • the data-processing system can be configured for receiving at least an indication of the corresponding target-data processing system for each set of measurement results.
  • the data-transmission component can be configured for receiving at least an indication of the corresponding target-data processing system for each set of measurement results.
  • the data-processing system can be configured for determining the target-set for each set of measurement results based on the target-data processing system corresponding to the respective set of measurement results.
  • the system can be configured for outputting at least one of the modified set(s) of measurement results.
  • the system can be configured for outputting the at least one of the modified set(s) of measurement results by means of the target-data processing systems respectively corresponding to the set(s) of measurement results.
  • the target-data processing system(s) can be configured for receiving the modified set(s) of measurement results.
  • the target-data processing system(s) can be configured for outputting the received set(s) of measurement results.
  • the data-processing system can be configured for transmitting instruction data.
  • the instruction data can comprise at least one or a plurality of measurement instruction set(s).
  • the data-processing system can be configured for receiving the measurement instruction set(s) and/or the instruction data from the target-data processing system(s).
  • the target-data processing system(s) can be configured for sending the measurement instruction set(s).
  • the data-processing system can be configured for transmitting the measurement instruction set(s) to the measurement-data processing system(s).
  • the measurement-data processing system(s) can be configured for generating the set(s) of measurement results based on the measurement instruction set(s).
  • Each measurement instruction set can comprise sample data.
  • the sample data of each instruction set can comprise a sample identifier, which sample identifier can be configured for identifying a sample to be analysed.
  • the measurement-data processing system(s) can be configured for transmitting at least the sample identifier of the measurement instruction set to the respective measurement equipment.
  • the respective measurement equipment can be configured for processing the sample corresponding to the sample identifier.
  • Each set of measurement results can comprise the sample identifier or an indicator thereof.
  • the measurement instruction set(s) can comprise at least one or a plurality of measurement instruction specifier(s).
  • the measurement instruction specifier(s) can be measurement specifier(s).
  • the data-processing system can be configured for receiving the measurement instruction set(s) from the target-data processing system(s).
  • the measurement instruction specifiers of the measurement instruction set(s) that the data-processing system receives can be according to the respective target-set.
  • the data-processing system can be configured for transmitting the measurement instruction specifiers of the measurement instruction set(s) to the measurement-data processing system(s) according to the respective origin-set.
  • the modification step can comprise modifying at least some of the measurement instruction specifiers so as to be according to the respective origin-set.
  • the modification step can comprise generating modified measurement instruction specifiers of measurement instruction set(s) whose respective origin-set and target-set are different.
  • the modification step can comprise generating modified versions of measurement instruction specifiers of the measurement instruction sets, which measurement instruction set(s) comprise different respective origin-sets and target-sets.
  • Generating the modified measurement instruction specifiers can be based on the association data.
  • Each of the set(s) of measurement results can comprise a target ID. Additionally or alternatively, each measurement instruction set can comprise a target ID. Each target ID can comprise an indication of the respective target-data processing system.
  • Each target ID can comprise an indication of the target set.
  • Each of the set(s) of measurement results can comprise an origin ID. Additionally or alternatively, each of the measurement instruction set(s) can comprise an origin ID. Each origin ID can comprise an indication of the respective measurement data-processing system.
  • Each origin ID can further comprise an indication of the origin set.
  • Generating the modified measurement instruction specifiers can further be based on the target ID and the origin ID.
  • Generating the modified set(s) of measurement results can further be based on the target ID and the origin ID.
  • the system can be configured to perform the method according to any of the method embodiments.
  • a first computer program product comprises instructions, which, when executed by a data- processing system and any of its components according to any of the above-disclosed embodiments of the system comprising the data-processing system, cause the data- processing system and its components to perform the steps, for which the data-processing system and its respective components are configured.
  • a second computer program product comprises instructions, which, when executed by the data-processing system and any of its components according to any of the above-disclosed embodiments of the system, cause the data-processing system and its respective components to perform the steps of the method according to any of the above-disclosed embodiments of the method, which method steps are performed by the data-processing system and the respective components according to the method.
  • a third computer program product comprising instructions, which, when executed by a measurement-data processing system as disclosed above, cause the measurement data- processing system to perform the method steps, which method steps are performed by the measurement data-processing system according to the above-disclosed method.
  • a method comprising processing measurement specifiers from a plurality of sets of measurement specifiers (21, 23, 24, 25, 26), wherein the plurality of sets of measurement specifiers (21, 23, 24, 25, 26) comprises at least a first set of measurement specifiers (21) and a second set of measurement specifiers (23).
  • association step comprises associating the measurement specifiers of the first set of measurement specifiers (21) to the measurement specifiers of the second set of measurement specifiers (23) respectively.
  • association step further comprises generating association data (30).
  • association data (30) comprise an association portion (35) indicating generated associations of measurement specifiers from different sets of measurement specifiers (21, 23, 24, 25, 26).
  • association step comprises associating measurement specifiers of the first set of measurement specifiers (21) to measurement specifiers from a plurality of the other sets of measurement specifiers (23, 24, 25, 26), respectively.
  • association step comprises associating measurement specifiers from a plurality of the sets of measurement specifiers (21, 23, 24, 25, 26) to measurement specifiers from the respectively other sets.
  • M10 The method according to any of the preceding embodiments with the features of M3, wherein the data-processing system comprises an association component, and wherein the association component performs the association step.
  • association step comprises associating said measurement specifiers by generating groups of corresponding measurement specifiers from different sets of measurement specifiers (21, 23, 24, 25, 26).
  • the measurement specifiers in each group may be from different sets of measurement specifiers.
  • an intermediary specifier can be assigned to a plurality of measurement specifiers from the plurality of sets.
  • the relation of the measurement specifiers to the intermediary specifiers can be a n-to-l-relation.
  • association data comprise an intermediary portion comprising the assignments of the indications of the intermediary specifiers to the measurement specifiers.
  • M20 The method according to any of the preceding method embodiments with the features of M18 and at least one of M4, M8 and M9, wherein the association step comprises associating the measurement specifiers from the sets of measurement specifiers by the assigned indicators of the intermediary specifiers.
  • association step comprises generating the association portion of the association data based on the assigned indicators from the intermediary portion.
  • pre-processing step comprises pre-processing specifiers from the sets of measurement specifiers (21, 23, 24, 25, 26).
  • pre-processing step further comprises pre-processing specifiers from the set of intermediary specifiers (22, 22', 22").
  • pre-processing a specifier comprises applying a removing criterion to the specifier and removing a portion of the specifier accordingly.
  • pre-processing a specifier comprises generating a hash-value for the specifier.
  • pre-processing a specifier comprises generating a plurality of different hash-values for the specifier.
  • M29 The method according to any of the preceding embodiments with the features of M22, wherein the pre-processing step comprises pre-processing the measurement specifiers, and wherein the method comprises loading and/or receiving a result of pre-processing the intermediary specifiers.
  • M30 The method according to any of the preceding method embodiments, wherein the method comprises a subset-selection step.
  • the subset-selection step comprises for each of a plurality of measurement specifiers to be associated, selecting a subset of the set of intermediary specifiers (22, 22', 22") based on a similarity of the respective measurement specifier and the intermediary specifiers.
  • the subset-selection step comprises determining the similarity by means of a similarity measure, wherein the similarity measure is based at least on a result of the pre-processing of the respective measurement specifier and the intermediary specifiers.
  • the similarity measure comprises an absolute value of a distance between the hash value(s) of the measurement specifiers and the intermediary specifiers.
  • selecting the subset of the set of intermediary specifiers (22, 22', 22") comprises selecting intermediary specifiers for which the similarity measure exceeds a subset-selection threshold (80).
  • selecting the subset of the set of intermediary specifiers (22, 22', 22") comprises selecting only intermediary specifiers for which the similarity measure exceeds the subset-selection threshold (80).
  • M39 The method according to any of the preceding method embodiments, preferably with the features of M18, wherein the method comprises performing a matching step.
  • M40 The method according to the preceding embodiment and with the features of M2, wherein the data-processing system comprises a matching component, and wherein the matching component performs the matching step.
  • the matching step comprises matching at least some of the measurement specifiers to corresponding intermediary specifiers.
  • the matching step comprises matching at least some of the measurement specifiers to corresponding intermediary specifiers by means of a comparison criterion.
  • the matching step further comprises assigning at least the indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • M45 The method according to any of the preceding embodiments with the features of M39, wherein the matching step comprises matching the measurement specifiers to the corresponding intermediary specifiers, and assigning at least an indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step comprises applying the comparison criterion to at least one pair of a measurement specifier and an intermediary specifier.
  • the matching step comprises applying the comparison criterion to a plurality of pairs, wherein each pair comprises a measurement specifier and an intermediary specifier.
  • M48 The method according to any of the two preceding embodiments and with the features of M30, wherein the matching step comprises applying the comparison criterion to the plurality of pairs, and wherein each pair comprises a measurement specifier and an intermediary specifier from the subset of intermediary specifiers selected for said measurement specifier.
  • the matching step comprises matching each measurement specifier only to an intermediary specifier, if, furthermore, a result of the comparison criterion exceeds a matching threshold (82).
  • M51 The method according to any of the preceding method embodiments with the features of M41 and Mil, wherein the method comprises associating the corresponding specifiers from the sets of measurement specifiers (21, 23, 24, 25, 26) based on the intermediary specifiers to which the measurement specifiers were matched.
  • M54 The method according to the preceding embodiment and with the features of M2, wherein the data-processing system generates the request data.
  • the matching step comprises generating request data for at least one measurement specifier for which no yielded matching probability exceeds the matching threshold.
  • the matching step comprises generating request data for at least one measurement specifier for which an application of the comparison criterion does not yield a corresponding intermediary specifier in the matching step.
  • M62 The method according to the preceding embodiment and with the features of M58, wherein the data-transmission component sends the request data.
  • M66 The method according to the preceding embodiment and with the features of M55, wherein the input pair(s) comprise the at least one measurement specifier corresponding to the at least one indication which the request data comprise.
  • M67 The method according to any of the three preceding embodiments, wherein the matching step further comprises matching at least one or at least some of the measurement specifiers to the corresponding intermediary specifier(s) based on the input data.
  • M68 The method according to any of the preceding four embodiments and with the features of M53, wherein the method comprises receiving at least a part of the input data after sending the request data.
  • M74 The method according to the preceding embodiment and with the features of M65, wherein the method comprises generating the alternative reference(s) of the at least one or the plurality of intermediary specifier(s) based at least on the pair(s) of measurement specifiers and corresponding intermediate specifiers from the matching-input data.
  • M75 The method according to any of the preceding method embodiments with the features of M70, wherein the method comprises receiving at least a portion of the alternative references from a second data-processing system.
  • M78 The method according to any of the preceding embodiments with the features of M2, wherein the data-processing system comprises a data-storage component, and wherein the data-storage component comprises persistent memory, such as a hard drive or a flash memory unit.
  • M84 The method according to any of the preceding method embodiments with the features of M73 and at least one of M42 and M41, wherein the method comprises generating at least some of the alternative reference(s) before finishing the subset-selection step for at least one set of measurement specifiers.
  • M86 The method according to the preceding embodiment and with the features of M2, wherein the data-processing system comprises a verification component, and wherein the verification component performs the verifying step.
  • the verifying step comprises verifying a compatibility of the respective measurement specifier to the respective intermediary specifier.
  • verifying said compatibility comprises verifying a compatibility of a measurement unit of the respective measurement specifier to a group of measurement units associated with the respective intermediary specifier.
  • verifying said compatibility comprises verifying a compatibility of an attribute of the respective measurement specifier to a group of attributes associated with the respective intermediary specifier.
  • M90 The method according to any of the two the preceding embodiments and with the features of M55, wherein, if the verifying step comes to a negative result for a measurement specifier and an intermediary specifier, the method comprises generating request data for the measurement specifier. M91. The method according to the preceding embodiment, wherein the generated request data further comprise at least an indication of the respective intermediary specifier.
  • each of the sets of measurement specifiers (21, 23, 24, 25, 26) is associated with at least one measurement-data processing system (64, 64').
  • M101 The method according to the preceding embodiment, wherein at least some of the measurement specifiers comprise attributes relating to a measurement procedure for generating measurement values specified by the respective measurement specifier.
  • M102 The method according to any of the preceding embodiments, wherein at least some of the measurement specifiers comprise a measurement unit or an indication thereof.
  • each data point comprises at least one value, and wherein each data point is according to a measurement specifier.
  • each set of measurement results (50, 51, 52) is initially according to a respective origin-set of the sets measurement specifiers (21, 23, 24, 25, 26).
  • M107 The method according to the preceding embodiment and with the features of M2, wherein the data-processing system comprises a modification component, and wherein the modification component performs the modification step.
  • modification step comprises generating modified set(s) of measurement results (50', 51', 52') so as to be each according to a respective target-set of the sets of measurement specifiers (21, 23, 24, 25, 26).
  • M109 The method according to the preceding embodiment, wherein for at least some sets of measurement results (50, 51, 52), the target-set is different from the origin-set.
  • Ml 10 The method according to the preceding embodiment and with the features of M5, preferably further with the features of M6, wherein generating the modified set(s) of measurement results is based on the association data.
  • generating the modified set(s) of measurement results (50, 51, 52) comprises generating modified data points of each of the set(s) of measurement results (50, 51, 52), which modified data points are according to the respective target-set of measurement specifiers.
  • Ml 13 The method according to any of the preceding embodiments with the features of M103 and M2, wherein the data-processing system receives the set(s) of measurement results (50, 51, 52).
  • M115 The method according to any of the preceding embodiments with the features of M103, wherein the method comprises receiving the set(s) of measurement results (50, 51, 52) from the at least one or a plurality of measurement-data processing system(s) (64, 64').
  • the measuring step comprises generating the set(s) of measurement results (50, 51, 52) by the measurement-data processing system(s) (64, 64').
  • each measurement-data processing system (64, 64') is connected to a respective set of measurement equipment, and wherein the method comprises transmitting measurement data from each set of measurement equipment to the corresponding measurement-data processing system (64, 64').
  • Ml 19 The method according to any of the three preceding embodiments, wherein a plurality of measurement results (50, 51, 52) from a same measurement- data processing system (64, 64') comprise the same origin-set.
  • M120 The method according to any of the four preceding embodiments, wherein all measurement results from same measurement-data processing systems (64, 64') comprise the same origin-set.
  • M121 The method according to any of the five preceding embodiments, wherein at least some measurement results (50, 51, 52) from different measurement-data processing systems (64, 64') comprise different origin-sets.
  • each set of measurement equipment (70, 70') comprises bio-medical measurement equipment.
  • M125 The method according to any of the preceding embodiments with the features of M108, wherein the method comprises transmitting the modified set(s) of measurement results (50, 51, 52).
  • M129 The method according to any of the three preceding embodiments, wherein the method comprises determining the target-set for each set of measurement results (50, 51, 52) based on the target-data processing system for the set of measurement results.
  • M130 The method according to any of the preceding embodiments with the features of M108, wherein the method comprises outputting at least one of the modified set(s) of measurement results (50, 51, 52).
  • M132 The method according to any of the preceding embodiments with the features of M125 and M2, wherein the data-processing system transmits the modified set(s) of measurement results (50, 51, 52).
  • the method comprises processing instruction data, wherein the instruction data comprise at least one or a plurality of measurement instruction set(s).
  • the measuring step comprises generating the set(s) of measurement result(s) (50, 51, 52) based on the measurement instruction set(s) by the measurement-data processing system(s) (64, 64').
  • each measurement instruction set comprises sample data
  • the sample data of each instruction set comprise (a) sample identifier(s) for (a) sample(s) to be analysed.
  • the measuring step comprises for each measurement instruction set, generating the respective set of measurement result(s) (50, 51, 52) by processing the sample(s) corresponding to the sample identifier(s) of the measurement instruction set.
  • each set of measurement results (50, 51, 52) comprises the sample identifier(s) or an indicator thereof.
  • the measurement instruction set(s) comprise at least one or a plurality of measurement instruction specifier(s), wherein the measurement instruction specifier(s) are measurement specifier(s).
  • M142 The method according to the preceding embodiment and with the features of M135, wherein the data-processing system receives the measurement instruction set(s) from the target-data processing system(s), and wherein the measurement instruction specifiers of the measurement instruction set(s) are initially according to the respective target-set.
  • modification step comprises modifying at least some of the measurement instruction specifiers by the data-processing system so as to be according to the respective origin-set.
  • modification step comprises generating modified measurement instruction specifiers of measurement instruction set(s) whose respective origin- set and target-set are different.
  • the measurement instruction set(s) comprises a target ID, wherein each target ID comprises an indication of the respective target-data processing system.
  • each target ID further comprises an indication of the target set.
  • the measurement instruction set(s) comprises an origin ID, wherein the origin ID comprises an indication of the respective measurement data- processing system.
  • each origin ID further comprises an indication of the origin set.
  • system embodiments are abbreviated by the letter “S” followed by a number. Whenever reference is herein made to the “system embodiments”, these embodiments are meant.
  • a system comprising a data-processing system, which data-processing system is configured for performing an association step.
  • the data-processing system further comprises an association component, and wherein the association component is configured for performing the association step.
  • the data-processing system further comprises a pre-processing component, wherein the pre-processing component is configured for performing a pre-processing step.
  • pre-processing component is further configured for performing a subset-selection step.
  • the data-processing system further comprises a matching component, and wherein the matching component is configured for performing a matching step.
  • the data-processing system comprises a verification component, wherein the verification component is configured for performing a verifying step.
  • the data-processing system further comprises a data-transmission component.
  • the system further comprises an output node.
  • the system comprises a second data-processing system.
  • the system comprises at least one or a plurality of measurement-data processing system(s) (64, 64').
  • the system comprises a set of measurement equipment.
  • each measurement-data processing system (64, 64’) comprises a connection to the respective set of measurement equipment.
  • the system comprises at least one or a plurality of target-data processing system(s).
  • the data-processing system is configured for processing measurement specifiers from a plurality of sets of measurement specifiers (21, 23, 24, 25, 26), wherein the plurality of sets of measurement specifiers (21, 23, 24, 25, 26) comprises at least a first set of measurement specifiers (21) and a second set of measurement specifiers (23).
  • association step comprises associating the measurement specifiers of the first set of measurement specifiers (21) to the measurement specifiers of the second set of measurement specifiers (23) respectively.
  • association step further comprises generating association data (30).
  • the association data (30) comprise an association portion (35), wherein the association portion is configured to indicate associations of measurement specifiers from different sets of measurement specifiers (21, 23, 24, 25, 26).
  • the plurality of sets of measurement specifiers (21, 23, 24, 25, 26) comprises further sets of measurement specifiers (24, 25, 26).
  • association step comprises associating measurement specifiers of the first set of measurement specifiers (21) to measurement specifiers from a plurality of the other sets of measurement specifiers (23, 24, 25, 26), respectively.
  • association step comprises associating measurement specifiers from a plurality of the sets of measurement specifiers (21, 23, 24, 25, 26) to measurement specifiers from the respectively other sets.
  • association step comprises associating said measurement specifiers by generating groups of corresponding measurement specifiers from different sets of measurement specifiers (21, 23, 24, 25, 26).
  • the measurement specifiers in each group may be from different sets of measurement specifiers.
  • corresponding measurement specifiers comprise corresponding biomarkers.
  • measurement specifiers from at least one group of corresponding measurement specifiers comprise different measurement units.
  • an intermediary specifier can be assigned to a plurality of measurement specifiers from the plurality of sets.
  • the relation of the measurement specifiers to the intermediary specifiers can be a n-to-l-relation.
  • association data comprise an intermediary portion comprising the assignments of the indications of the intermediary specifiers to the measurement specifiers.
  • association step comprises associating the measurement specifiers from the sets of measurement specifiers by the assigned indicators of the intermediary specifiers.
  • association step comprises generating the association portion of the association data based on the assigned indicators from the intermediary portion.
  • pre-processing step comprises pre-processing specifiers from the sets of measurement specifiers (21, 23, 24, 25, 26).
  • pre-processing step further comprises pre-processing specifiers from the set of intermediary specifiers (22, 22', 22").
  • pre-processing a specifier comprises applying a removing criterion to the specifier and removing a portion of the specifier accordingly.
  • pre-processing a specifier comprises generating a hash-value for the specifier.
  • pre-processing a specifier comprises generating a plurality of different hash-values for the specifier.
  • pre-processing step comprises pre-processing the measurement specifiers, and wherein the data-processing system is configured for loading and/or receiving a result of pre-processing the intermediary specifiers.
  • the pre-processing step comprises the subset-selection step.
  • the system according to the preceding embodiment, wherein the plurality of measurement specifiers to be associated is a plurality of measurement specifiers to be associated to corresponding measurement specifiers.
  • the subset-selection step comprises determining the similarity by means of a similarity measure, wherein the similarity measure is based at least on a result of the pre-processing of the respective measurement specifier and the intermediary specifiers.
  • the similarity measure is based at least on the hash-values generated for the specifiers.
  • the similarity measure comprises an absolute value of a distance between the hash value(s) of the measurement specifiers and the intermediary specifiers.
  • selecting the subset of the set of intermediary specifiers (22, 22', 22") comprises selecting intermediary specifiers for which the similarity measure exceeds a subset-selection threshold (80).
  • selecting the subset of the set of intermediary specifiers (22, 22', 22") comprises selecting only intermediary specifiers for which the similarity measure exceeds the subset-selection threshold (80).
  • the system according to any of the preceding system embodiments preferably with the features of S30, wherein the system comprises the features of S5.
  • the matching step comprises matching at least some of the measurement specifiers to corresponding intermediary specifiers.
  • the matching step comprises matching at least some of the measurement specifiers to corresponding intermediary specifiers by means of a comparison criterion.
  • matching the at least some of the measurement specifiers to corresponding intermediary specifiers is based at least one the subsets of the intermediary specifiers respectively selected for the measurement specifiers.
  • the matching step further comprises assigning at least the indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step comprises matching the measurement specifiers to the corresponding intermediary specifiers, and assigning at least an indication of the matched intermediary specifiers to the corresponding measurement specifiers.
  • the matching step comprises applying the comparison criterion to at least one pair of a measurement specifier and an intermediary specifier.
  • the matching step comprises applying the comparison criterion to a plurality of pairs, wherein each pair comprises a measurement specifier and an intermediary specifier.
  • the matching step comprises applying the comparison criterion to the plurality of pairs, and wherein each pair comprises a measurement specifier and an intermediary specifier from the subset of intermediary specifiers selected for said measurement specifier.
  • the matching step comprises matching each measurement specifier to the intermediary specifier for which the comparison criterion yields a maximum matching probability.
  • the matching step comprises matching each measurement specifier only to an intermediary specifier, if, furthermore, a result of the comparison criterion exceeds a matching threshold (82).
  • the data-processing system preferably the association component
  • the data-processing system is configured for associating the corresponding specifiers from the sets of measurement specifiers (21, 23, 24, 25, 26) based on the intermediary specifiers to which the measurement specifiers were matched.
  • the data-processing system preferably the association component, is configured associating the measurement specifiers from the sets of measurement specifiers (21, 23, 24, 25, 26) which measurement specifiers were matched to same intermediary specifiers respectively.
  • the data-processing system is configured for generating request data.
  • the data-processing system is configured for sending the request data.
  • the data-processing system is configured for sending the request data to an output-node, and wherein the output-node comprises an output interface.
  • the output-node is configured for outputting data.
  • the output-node is configured for outputting request data.
  • the data-transmission component is configured for sending the request data.
  • the data-processing system is configured for receiving input data.
  • the data-transmission component is configured for receiving the input data.
  • the input data comprise at least one or a plurality of input pair(s), and wherein each input pair comprises a measurement specifier and a corresponding intermediate specifier.
  • the input pair(s) comprise the at least one measurement specifier corresponding to the at least one indication which the request data comprise.
  • the matching step further comprises matching at least one or at least some of the measurement specifiers to the corresponding intermediary specifier(s) based on the matching-input data.
  • the data-processing system or the data-transmission component is configured for receiving the matching-input data after sending the request data.
  • each intermediary specifier comprises a reference.
  • at least one or a plurality of intermediary specifier(s) further comprise at least one or a plurality of alternative reference(s).
  • the data-processing system is configured for receiving at least a portion of the alternative references from a second data-processing system.
  • the data-processing system is configured for storing the alternative references.
  • the data-storage component comprises persistent memory, such as a hard drive or a flash memory unit.
  • the subset-selection step and the matching step comprise(s) generating at least some of the alternative reference(s), and wherein the data-processing system is configured for using the alternative reference(s) in a subsequent operation.
  • the matching component and the pre-processing component are configured for generating at least some of the alternative reference(s).
  • the system according to any of the preceding method embodiments with the features of S80 and at least one of S49 and S50, wherein the data-processing system is configured for generating at least some of the alternative reference(s) before matching measurement specifiers from at least one set of measurement specifiers to the corresponding intermediary specifiers.
  • the method according to any of the preceding method embodiments with the features of S80 and at least one of S49 and S50, wherein the data-processing system is configured for generating at least some of the alternative reference(s) before finishing the subset-selection step for at least one set of measurement specifiers.
  • the matching step comprises the verifying step, and wherein the matching component comprises a verification component.
  • the verifying step comprises verifying a compatibility for each of a plurality of the measurement specifiers to the respective intermediary specifier(s).
  • verifying said compatibility comprises verifying a compatibility of a measurement unit of the measurement specifier to a group of measurement units associated with the respective intermediary specifier(s).
  • verifying said compatibility comprises verifying a compatibility of an attribute of the respective measurement specifier to a group of attributes associated with the respective intermediary specifier.
  • applying the comparison criterion comprises processing a result of the verifying step for the measurement specifier and the intermediary specifier.
  • the measurement specifiers comprise attributes relating to a measurement procedure for generating measurement values specified by the respective measurement specifier.
  • SI 10 The system according to any of the preceding system embodiments with the features of S16, wherein the data-processing system is configured for receiving at least one or a plurality of set(s) of measurement results (50, 51, 52), wherein each set of measurement results (50, 51, 52) comprises at least one or a plurality of data points.
  • each data point comprises at least one value, and wherein each data point is according to a measurement specifier.
  • SI 12 The system according to any of the two preceding embodiments, wherein each set of measurement results (50, 51, 52) is initially according to a respective origin-set of the sets measurement specifiers (21, 23, 24, 25, 26).
  • SI 13 The system according to the preceding embodiment and with the features of S7, wherein the modification step comprises generating modified set(s) of measurement results (50', 51', 52') so as to be each according to a respective target-set of the sets of measurement specifiers (21, 23, 24, 25, 26).
  • SI 14 The system according to the preceding embodiment, wherein for at least some sets of measurement results (50, 51, 52), the target-set is different from the origin-set.
  • generating the modified set(s) of measurement results (50, 51, 52) comprises generating modified data points of each of the set(s) of measurement results (50, 51, 52), wherein the modified data points are according to the respective target-set of measurement specifiers.
  • SI 17 The system according to the preceding embodiment and with the features of S109, wherein generating the modified data points further comprises converting at least one of the data points to a measurement unit of the corresponding measurement specifier of the target-set.
  • SI 19 The system according to any of the preceding embodiments and with the features of S110, S12 and preferably S9, wherein the data-processing system, preferably the data-transmission component, is configured for receiving the set(s) of measurement results (50, 51, 52) from the measurement-data processing system(s) (64, 64').
  • the data-processing system preferably the data-transmission component
  • each set of measurement equipment (70, 70') comprises bio-medical measurement equipment.
  • each set of measurement equipment (70, 70’) is configured for generating a part of the measurement data.
  • the target-data processing system(s) (64, 64') are configured for receiving the modified set(s) of measurement results (50, 51, 52), and wherein the target-data processing system(s) (64, 64') are configured for outputting the received set(s) of measurement results (50, 51, 52).
  • the data-processing system is configured for processing and/or transmitting instruction data, wherein the instruction data comprise at least one or a plurality of measurement instruction set(s).
  • each measurement instruction set comprises sample data
  • the sample data of each instruction set comprise a sample identifier for a sample to be analysed.
  • the measurement-data processing system(s) 64, 64’ are configured for transmitting at least the sample identifier of the measurement instruction set to the respective measurement equipment, and wherein the respective measurement equipment is configured for processing the sample corresponding to the sample identifier.
  • each set of measurement results (50, 51, 52) comprises the sample identifier or an indicator thereof.
  • the measurement instruction set(s) comprise at least one or a plurality of measurement instruction specifier(s), wherein the measurement instruction specifier(s) are measurement specifier(s).
  • modification step comprises generating modified measurement instruction specifiers of measurement instruction set(s) whose respective origin- set and target-set are different.
  • the measurement instruction set(s) comprises a target ID, wherein each target ID comprises an indication of the respective target-data processing system.
  • each target ID further comprises an indication of the target set.
  • the measurement instruction set(s) comprises an origin ID, wherein the origin ID comprises an indication of the respective measurement data- processing system. 5152.
  • a computer program product comprising instructions, which, when executed by a data-processing system and any of its components according to any of the system embodiments, cause the data-processing system and its components to perform the steps, for which the data-processing system and/or any of its components are configured.
  • a computer program product comprising instructions, which, when executed by the data-processing system and any of its components according to any of the system embodiments, cause the data-processing system and its respective components to perform the steps of the method according to any of the method embodiments, which method steps are performed by the data-processing system and/or the respective components according to the method.
  • a computer program product comprising instructions, which, when executed by a measurement-data processing system according to any of the system embodiments with the features of S12, cause the measurement data-processing system to perform the method steps, which method steps are performed by the measurement data-processing system according to the method. Exemplary features of the invention are further detailed in the figures and the below description of the figures.
  • Fig. 1 shows a function and components of a system
  • Fig. 2 shows further components of the system
  • Fig. 3 shows sets of specifiers and an association portion of association data
  • Fig. 4 shows groups of specifiers of different sets
  • Figure 1 shows a system comprising a data-processing system 10, which data-processing system 10 can comprises different components and is configured for processing data.
  • the data-processing system can inter alia process association data 30.
  • the data-processing system 10 can be configured to allow for connection of other systems using different or incompatible data structures for processing measurements and/or instructions to perform said measurements.
  • FIG. 80 shows target-data processing systems 80, 81, 82. These target-data processing systems can be configured for generating measurement instruction sets 55, 56, 57. Each measurement instruction set can be according to an encoding 40, 42 of the measurement instructions.
  • the target-data processing systems 80, 82 can operate using at least an encoding A, 40, for their measurement instruction sets.
  • the target-data processing system 81 can operate using at least another encoding C, 42.
  • These encodings can be specified, our they can be implicit, e.g. a structure and a set of used instructions, used by a target-data processing system.
  • An example for a data-processing system can be data-processing system in a quality control of a production facility, for example a facility for the production of chemical or pharmaceutical compounds.
  • measurements such as a chemical or bio chemical analysis of samples of produced substances, may be necessary.
  • a production facility is not limited to one continuous production process for one substance, but there may be multiple process steps. Of these, some may require different measurements.
  • a production facility may produce different substances, hence, for different substances, different measurements may be necessary.
  • the target-data processing systems can be configured for generating the sets of measurement instructions 55, 56, 57. These sets 55, 56, 57 can each be configured to be interpreted by measurement-data processing systems 64, 64', 64".
  • a corresponding measurement-data processing system 64, 64', 64" can be configured for generating measurement data, such as sets measurement results 50, 51, 52.
  • a measurement-data processing system 64, 64', 64" can be configured for generating a set of measurement results 50, 51, 52 based on a measurement instruction set.
  • a measurement-data processing system can also use at least one encoding for the sets of measurement results 50, 51, 52.
  • the measurement-data processing systems 64, 64" can use the encoding C, 42
  • the measurement-data processing system 64' can use the encoding A, 40.
  • the measurement-data processing systems can use different encodings and that the encodings may be different from encodings used by the target-data processing systems.
  • the person skilled in the art will also easily understand that all measurement-data processing systems may use a same encoding.
  • the measurement-data processing system 64, 64', 64" can be configured for transmitting a respective set of measurement results 50, 51, 52 to a respective target-data processing system 80, 81, 82.
  • the measurement instruction sets 55, 56, 57 can each relate to a sample.
  • the sample can be a sample of a produced good.
  • the sample can for example be a sample of tissue of fluid, originating from a patient.
  • Each sample can comprise an ID.
  • the ID can be configured to identify the sample.
  • the ID can for example be a number, a barcode, a QR-code or another visual marking relating to the sample.
  • a container of the sample can comprise this identifier.
  • the identifier can also be an RFID-tag or another marking, which the container can comprise.
  • Methods for marking sample containers individually are well-known in the ask.
  • An example for visual markings can be found in WO98/05427, which in incorporated herein by reference.
  • the container(s) of the sample(s) can be marked with the ID by laser radiation.
  • At least one group of the target-data processing systems 80, 81, 82 and the measurement- data processing systems 64, 64', 64" can be configured for at least partially automated processing of the measurement instruction sets and/or the measurement results.
  • the measurement-data processing system(s) 64, 64', 64" can be configured for processing measurement instruction set(s) that they receive respectively.
  • the measurement instruction set(s) 55, 56, 57 would have to be according to an encoding that the respective measurement-data processing system 64, 64', 64" is configured to process.
  • measurement-data processing systems for example different laboratories or laboratory information systems
  • target data-processing systems for example data-processing systems in a production facility or at a health care provider.
  • measurement-data processing systems 64", 64', 64 which use different encoding(s) 40, 41, 42 than respectively corresponding target-data processing systems 80, 81, 82.
  • an increased interoperability can be optionally advantageous, for example in a case where a measuring facility operating one of the measurement-data processing systems 64, 64', 64" cannot provide a certain measurement.
  • This can for example be the case temporarily, e.g. due to an increased backlog of measurements, technical problems, a temporary unavailability of substances necessary for testing or maintenance.
  • This can also be permanently the case, e.g. when a certain measurement facility does not perform a certain test, measurement or analysis at all, for example if the facility lacks a certain machine or another piece of measurement equipment.
  • the data-processing system 10 can be configured for generating modified measurement instruction sets 55', 56', 57' based on received measurement instruction sets 55, 56, 57. Particularly, the data-processing system 10 can be configured for generating the modified measurement instruction sets 55', 56', 57' in cases where the measurement-data processing system 64, 64', 64" is configured for processing instruction in an encoding different from the respective encoding of the measurement instruction sets 55, 56, 57.
  • the data-processing system 10 can also be configured for generating the modified sets of measurement results 50', 51', 52', particularly in cases where the target-data processing system 80, 81, 82 receiving the sets is configured for processing sets of measurement results corresponding to a different encoding.
  • the data-processing system 10 can be configured to do so based on a association data 30.
  • the association data can comprise associations of specifiers of different encodings.
  • An encoding in this context can comprise or specify at least one set of measurement specifiers 21, 22, 23, 24, 25, 25.
  • Each measurement specifier can be configured specify a measurement, which can for example relate to a test, an analysis or a direct measurement.
  • the measurement specifiers can also be configured to specify a respective result of such a measurement.
  • the measurement instruction sets 55, 56, 57, 55', 56', 57' can each be according to measurement specifiers.
  • the measurement results 50, 51, 52, 50', 51', 52' can each be according to measurement specifiers.
  • the data-processing system 10 can comprise at least one component.
  • the data-processing system can comprise an association component 11.
  • the association component can be configured for generating at least a part of the association data 30. This can be optionally advantageous as the system may then not or at least not entirely rely on association data 30 provided by a third entity. Hence, integration efforts can be reduced.
  • association component 30 can be configured for successively generating the association data 30.
  • the data-processing system 10 can further comprise a pre-processing component 12.
  • the pre-processing component 12 can be configured for pre-processing specifiers, such as measurement specifiers 21, 23, 24, 25, 26 and/or intermediary specifiers 22, as discussed in the description.
  • the data-processing system 10 can also comprise a verification component 13.
  • the verification component can be configured for performing a verifying step.
  • the verification step can comprise verifying a compatibility of specifiers 21, 22, 23, 24, 25, 26, for example based on a unit associated therewith.
  • the data-processing system 10 can comprise a modification component 14.
  • the modification component 14 can be configured for performing a modification step.
  • the modification step can be configured for modifying at least one of the sets of measurement results 50, 51, 52 and the measurement instruction sets 55, 56, 57, so as to respectively generate the modified sets of measurement results 50', 51', 52' and/or the modified measurement instruction sets 55', 56', 57'.
  • the data-processing system 10 can comprise a data-storage component 15.
  • the data storage component can be configured for storing data, preferably on persistent memory.
  • the data-processing system 10 can further comprise a data-transmission component 16.
  • the data-transmission component can be configured for sending and receiving data.
  • the data-transmission component can be configured for receiving the sets of measurement results 50, 51, 52.
  • the data-transmission component can also be configured for sending the measurement results and/or modified measurement results 50', 51', 52'.
  • the data-transmission component 16 can be configured for receiving the measurement instruction sets 55, 56, 57.
  • the data-transmission component 16 can also be configured for sending the measurement results and/or the modified measurement instruction sets 55', 56', 57'.
  • the measurement-data processing systems 64, 64', 64" can be configured for generating the sets of measurement results.
  • each measurement-data processing system 64, 64' can be configured to be connected to a respective set of measurement equipment 70, 70'.
  • the set of measurement equipment can comprise machinery, devices and items for generating the measurements.
  • the connection can be automated, e.g. data exchange via a Local Area Network.
  • there can also be an agent, operating the respective set of measurement equipment 70,70' according to instructions from the measurement-data processing system and/or inputting generated measurement data to the respective measurement-data processing system 64, 64'.
  • the target-data processing systems 80, 81 can be configured for receiving an identifier of a sample which is then transported to the measurement facilities. Data generated by the measurement-data processing systems 64, 64’ can be transmitted to a corresponding or to another target-data processing system 80, 81.
  • the target-data processing systems 80, 81 and/or the measurement-data processing systems 64, 64’ be connected to the data-processing system 10.
  • the measurement-data processing system 64, 64’ and/or the target-data processing system can comprise a connection to the data-processing system 10.
  • the connection can be at least one of direct and indirect.
  • Figure 3 shows sets of measurement specifiers 21, 23, 24, 25, 26, and a set of intermediary specifiers 22.
  • Each set of specifiers comprises specifiers for specifying measurements, wherein measurements can be understood as discussed above, hence for example also comprising physical, chemical or bio-chemical analyses.
  • the sets of specifiers can correspond to encodings, such as the encoding A 40, the encoding B 41, and the encoding C 42.
  • the encoding B, to which the intermediary specifiers can corresponding can be a standard encoding.
  • An encoding can for example comprise specifiers. It can also comprise a format and/or a logic for a use of the specifiers.
  • the intermediary specifiers 22 can also be used by a measurement-data processing system 64, 64’, 64" and/or a target-data processing system 70, 70’, 70".
  • a measurement-data processing system 64, 64’, 64" and/or a target-data processing system 70, 70’, 70" can use the intermediary specifiers 22, which can be according to a standard encoding.
  • the association portion 35 can be configured for specifying a relation of the specifiers from the different sets of specifiers 21, 22, 23, 24, 25, 26. For example, for a specifier from the first set of measurement specifiers 21, a corresponding specifier from the second set of measurement specifiers 23 may be indicated by the association portion 35.
  • Figure 4 details on a relation of the specifiers of the different sets of specifiers. Particularly, Figure 4 details on groups of specifiers, wherein the groups of specifiers can comprise corresponding specifiers from different sets of specifiers 21, 22, 23, 24, 25, 26.
  • the sets of specifiers 21, 22, 23, 24 comprise specifiers, indicated by long, horizontally oriented rectangles. Dashed lines indicate groups of corresponding specifiers. The groups can comprise corresponding specifiers from different sets of specifiers. Corresponding specifiers can for example specify corresponding measurements. However, corresponding specifiers do not need to specify same units or formats for results of said measurements. As an example, a length of a sample to be measured can be indicated in the first set of measurement specifiers 21 in inch and in the second set of measurement specifiers 23 in cm.
  • the set of intermediary specifiers 22 may comprise a list of units for each specifier. The list can be a list of compatible units, that is, units configured to specify a corresponding variable.
  • each group comprise an intermediary specifier.
  • the data-processing system can be configured for matching each measurement specifier to an intermediary specifier, and, based on this matching, for generating an association of measurement specifiers from different sets of measurement specifiers, that is for example the groups shown in Fig. 4.
  • An optional advantage can be that the association data 30, preferably the association portion 35, can comprise the associations of measurement specifiers to other measurement specifiers or that these can be directly derived from the association data 30, preferably from the association portion 35.
  • generating modified specifiers e.g. for generating a modified set of measurement results 50', 51', 52' or for generating a modified set of measurement instructions 55', 56', 57', the respective data can directly be transformed.
  • This can be optionally advantageous, as it may not need to be transformed to a standard format first.
  • This can be optionally advantageous, as it may save a computer-implemented method step, using memory and/or computing time.
  • a corresponding intermediary specifier can be added either automatically or a human operator can be instructed to verify and add an intermediary specifier.
  • step (A) precedes step (B) this does not necessarily mean that step (A) precedes step (B), but it is also possible that step (A) is performed (at least partly) simultaneously with step (B) or that step (B) precedes step (A).
  • step (X) preceding step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Yl), ..., followed by step (Z).
  • step (X) preceding step (Z) encompasses the situation that step (X) is performed directly before step (Z), but also the situation that (X) is performed before one or more steps (Yl), ..., followed by step (Z).

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Abstract

La présente invention concerne un procédé comprenant le traitement de spécificateurs de mesure à partir d'une pluralité d'ensembles de spécificateurs de mesure. La pluralité d'ensembles de spécificateurs de mesure comprend au moins un premier ensemble de spécificateurs de mesure et un second ensemble de spécificateurs de mesure. Le procédé comprend en outre l'exécution d'une étape d'association. L'étape d'association consiste à associer des spécificateurs de mesure correspondants du premier ensemble de spécificateurs de mesure à des spécificateurs de mesure à partir d'une pluralité de l'autre ensemble ou des autres ensembles de spécificateurs de mesure, respectivement. L'étape d'association consiste en outre à attribuer à certains ou à tous les spécificateurs de mesure des ensembles de spécificateurs de mesure une indication d'un spécificateur intermédiaire correspondant d'un ensemble de spécificateurs intermédiaires, respectivement. Le procédé comprend également un procédé de sélection de sous-ensembles. L'étape de sélection de sous-ensembles consiste, pour chaque spécificateur d'une pluralité de spécificateurs de mesure à associer, à sélectionner un sous-ensemble de l'ensemble de spécificateurs intermédiaires sur la base d'une similarité du spécificateur de mesure respectif et des spécificateurs intermédiaires. Le procédé comprend en outre l'exécution d'une étape de mise en correspondance, l'étape de mise en correspondance consistant à mettre en correspondance au moins certains des spécificateurs de mesure avec des spécificateurs intermédiaires correspondants sur la base d'au moins l'un des sous-ensembles des spécificateurs intermédiaires sélectionnés respectivement pour les spécificateurs de mesure. Au moins certains des spécificateurs de mesure comprennent des attributs se rapportant à une procédure de mesure pour générer des valeurs de mesure spécifiées par le spécificateur de mesure respectif. L'invention concerne en outre un système. Le système comprend un système de traitement de données. Le système de traitement de données est configuré pour exécuter une étape d'association. L'invention concerne également des produits-programmes informatiques correspondants pour le système de traitement de données.
PCT/EP2021/052005 2020-01-30 2021-01-28 Système et procédé de traitement de données de mesure WO2021152022A1 (fr)

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