CN109003670A - Big data medical information processing method, system, terminal device and storage medium - Google Patents
Big data medical information processing method, system, terminal device and storage medium Download PDFInfo
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- CN109003670A CN109003670A CN201810710948.4A CN201810710948A CN109003670A CN 109003670 A CN109003670 A CN 109003670A CN 201810710948 A CN201810710948 A CN 201810710948A CN 109003670 A CN109003670 A CN 109003670A
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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Abstract
The invention discloses a kind of big data medical information processing method, system, terminal device and storage mediums, which comprises acquires the medical information of user, the medical information includes audit report information and label information；The characteristic information in the audit report information is extracted, feature vector is generated according to the characteristic information；Described eigenvector is compared with characteristic information in the diagnostic model for having big data, the corresponding targeted diagnostics result information of described eigenvector is determined according to comparison result；Corresponding historical diagnostic result information is searched according to the label information, the targeted diagnostics result is verified according to historical diagnostic result information；When verification result is matching, the targeted diagnostics result information is shown.The audit report of user is compared by the present invention by terminal device with the characteristic information in default diagnostic model, determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
Description
Technical field
The present invention relates to terminal device technical field more particularly to a kind of big data medical information processing methods, system, end
End equipment and storage medium.
Background technique
Currently, more and more in short supply in face of medical treatment outfit, the requirement to medical services is also higher and higher, the technology of diagnosis
Also irregular, also, traditional mode seen a doctor of registering also is to rely on now for the diagnosis of disease, in diagnosis mistake
In the case where accidentally, the physiology and psychology of patient are impacted, is unfavorable for the sound development of society, will also result in doctor-patient relationship
Anxiety.
Summary of the invention
It is a primary object of the present invention to propose a kind of big data medical information processing method, system, terminal device and deposit
Storage media, it is intended to the technical issues of solution cannot achieve intelligentized medical diagnosis on disease in the prior art.
To achieve the above object, the present invention provides a kind of big data medical information processing method, the big data medical treatment letter
Cease processing method the following steps are included:
The medical information of user is acquired, the medical information includes audit report information and label information；
The characteristic information in the audit report information is extracted, feature vector is generated according to the characteristic information；
Described eigenvector is compared with characteristic information in the diagnostic model for having big data, it is true according to comparison result
Determine the corresponding targeted diagnostics result information of described eigenvector；
Corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic result information to described
Targeted diagnostics result is verified；
When verification result is matching, the targeted diagnostics result information is shown.
Preferably, the characteristic information extracted in the audit report information generates feature according to the characteristic information
Vector specifically includes:
The sampling area in the audit report information is extracted, the characteristic information that the sampling area acquires is passed through into SIFT
Algorithm generates feature vector.
Preferably, the sampling area extracted in the audit report information, the feature that the sampling area is acquired
Before information generates feature vector by SIFT algorithm, the method also includes:
Reference inspection report information is obtained, the reference inspection report information is subjected to format conversion, is converted to default lattice
Formula, the preset format carry sampling area.
Preferably, described to be compared described eigenvector with characteristic information in the diagnostic model for having big data, root
Before determining the corresponding targeted diagnostics result information of described eigenvector according to comparison result, the method also includes:
The corresponding relationship for obtaining the feature vector of big data and the diagnostic result of big data generates the corresponding relationship big
The diagnostic model of data.
Preferably, described that corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic knot
Before fruit information verifies the targeted diagnostics result, the method also includes:
The relation mapping table for prestoring history tab information and corresponding historical diagnostic result information, according to the relationship
Mapping table, which is executed, searches corresponding historical diagnostic result information according to the label information, according to historical diagnostic result information to institute
Targeted diagnostics result is stated to be verified.
Preferably, described that corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic knot
Fruit information verifies the targeted diagnostics result, specifically includes:
Corresponding historical diagnostic result information is searched according to the label information, is not searching the historical diagnostic result letter
When breath, diagnostic result information corresponding with other matched label informations of described eigenvector is searched to the targeted diagnostics result
It is verified.
Preferably, before the medical information of the acquisition user, the method also includes:
Judge whether the medical information is legal, when the medical information is legal, executes the medical information of acquisition user.
In addition, to achieve the above object, the present invention also proposes a kind of big data medical information processing system, the big data
Medical information processing system includes:
Acquisition module, for acquiring the medical information of user, the medical information includes audit report information and label letter
Breath；
Extraction module generates special for extracting the characteristic information in the audit report information according to the characteristic information
Levy vector；
Comparison module, for described eigenvector to be compared with characteristic information in the diagnostic model for having big data,
The corresponding targeted diagnostics result information of described eigenvector is determined according to comparison result；
Authentication module, for searching corresponding historical diagnostic result information according to the label information, according to historical diagnostic
Result information verifies the targeted diagnostics result；
Display module, for when verification result is matching, the targeted diagnostics result information to be shown.
In addition, to achieve the above object, the present invention also proposes a kind of terminal device, the terminal device include: memory,
Processor and the big data medical information processing routine that is stored on the memory and can run on the processor, it is described
The step of big data medical information processing routine is arranged for carrying out big data medical information processing method as described above.
In addition, to achieve the above object, the present invention also proposes a kind of storage medium, big number is stored on the storage medium
According to medical information processing routine, as described above big is realized when the big data medical information processing routine is executed by processor
The step of data medical information processing method.
Big data medical information processing method proposed by the present invention by the audit report of user and is preset by terminal device
Characteristic information in diagnostic model is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis
Efficiency.
Detailed description of the invention
Fig. 1 is the terminal device structural schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram of big data medical information processing method first embodiment of the present invention；
Fig. 3 is the flow diagram of big data medical information processing method second embodiment of the present invention；
Fig. 4 is the flow diagram of big data medical information processing method 3rd embodiment of the present invention；
Fig. 5 is the functional block diagram of big data medical information processing system first embodiment of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
Referring to Fig.1, Fig. 1 is the terminal device structural schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
As shown in Figure 1, the terminal device may include: processor 1001, such as CPU, communication bus 1002, user interface
1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), input unit such as key, and optional user interface 1003 can also wrap
Include standard wireline interface and wireless interface.Network interface 1004 optionally may include standard wireline interface and wireless interface
(such as WI-FI interface).Memory 1005 can be high speed RAM memory, be also possible to stable memory (non-volatile
), such as magnetic disk storage memory.Memory 1005 optionally can also be the storage dress independently of aforementioned processor 1001
It sets.
It will be understood by those skilled in the art that terminal device structure shown in Fig. 1 does not constitute the limit to terminal device
It is fixed, it may include perhaps combining certain components or different component layouts than illustrating more or fewer components.
As shown in Figure 1, as may include operating system, network communication mould in a kind of memory 1005 of storage medium
Block, Subscriber Interface Module SIM and big data medical information processing routine.
In terminal device shown in Fig. 1, network interface 1004 is mainly used for connecting terminal device, carries out with terminal device
Data communication；User interface 1003 is mainly used for connecting user terminal, carries out data communication with terminal；Terminal device of the present invention is logical
It crosses processor 1001 and calls the big data medical information processing routine stored in memory 1005, and execute following operation:
The medical information of user is acquired, the medical information includes audit report information and label information；
The characteristic information in the audit report information is extracted, feature vector is generated according to the characteristic information；
Described eigenvector is compared with characteristic information in the diagnostic model for having big data, it is true according to comparison result
Determine the corresponding targeted diagnostics result information of described eigenvector；
Corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic result information to described
Targeted diagnostics result is verified；
When verification result is matching, the targeted diagnostics result information is shown.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
The sampling area in the audit report information is extracted, the characteristic information that the sampling area acquires is passed through into SIFT
Algorithm generates feature vector.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
Reference inspection report information is obtained, the reference inspection report information is subjected to format conversion, is converted to default lattice
Formula, the preset format carry sampling area.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
The corresponding relationship for obtaining the feature vector of big data and the diagnostic result of big data generates the corresponding relationship big
The diagnostic model of data.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
The relation mapping table for prestoring history tab information and corresponding historical diagnostic result information, according to the relationship
Mapping table, which is executed, searches corresponding historical diagnostic result information according to the label information, according to historical diagnostic result information to institute
Targeted diagnostics result is stated to be verified.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
Corresponding historical diagnostic result information is searched according to the label information, is not searching the historical diagnostic result letter
When breath, diagnostic result information corresponding with other matched label informations of described eigenvector is searched to the targeted diagnostics result
It is verified.
Further, processor 1001 can call the big data medical information processing routine stored in memory 1005,
Also execute following operation:
Judge whether the medical information is legal, when the medical information is legal, executes the medical information of acquisition user.
The present embodiment through the above scheme, by terminal device by the spy in the audit report of user and default diagnostic model
Reference breath is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
Based on above-mentioned hardware configuration, big data medical information processing method embodiment of the present invention is proposed.
It is the flow diagram of big data medical information processing method first embodiment of the present invention referring to Fig. 2, Fig. 2.
In the first embodiment, the big data medical information processing method the following steps are included:
Step S10, acquires the medical information of user, and the medical information includes audit report information and label information.
In the present embodiment, it is based on a set of medical diagnosis system, the medical diagnosis system includes each diagnostic device, example
Such as B ultrasound equipment, CT scan (Computed Tomography, CT) equipment etc. may also include other medical treatment and examine
Disconnected equipment, with no restriction to this, in the present system, the Medical Devices are interconnected the present embodiment, can carry out data communication, are cured
Treat equipment by diagnostic message send in terminal process equipment in the present embodiment, the medical information is analyzed and processed.
In the concrete realization, for the ease of the management for medical information, Medical Devices acquisition user diagnostic message it
The diagnostic message is put on to the label of user afterwards, so that the differentiation with other users, can also carry out user by other means
Mark, the present embodiment to this with no restriction.
Step S20 extracts the characteristic information in the audit report information, according to the characteristic information generate feature to
Amount.
In the concrete realization, by acquiring each information point, by each information point composition characteristic vector, firstly, being reported according to checking
The data generation characteristic information for presetting item in information is accused, such as in the ultrasound diagnosis of stomach, stomach and peripheral part are detected
Echo size and shape size, being for echo size therefore can be big by echo for the key reference factor of inspection result
Small data may also include other crucial parameter informations as characteristic information, by the parameter information of acquisition generate feature to
Amount, so as to pass through the key parameter in characteristic vector pickup report information.
Described eigenvector is compared by step S30 with characteristic information in the diagnostic model for having big data, according to than
The corresponding targeted diagnostics result information of described eigenvector is determined compared with result.
It should be noted that in the present embodiment, the diagnostic model of the diagnostic model equipped with big data, the big data is set
There are different characteristic information and corresponding diagnostic result, the medical diagnosis on disease information of decades is included substantially, thus to medical diagnosis on disease
Effectively reference frame is provided.
In the concrete realization, feature vector can be put into the big data with diagnostic model in be iterated and match, obtain
To corresponding diagnostic result, to reduce the one-sidedness of personal diagnosis and reduce the error rate of diagnosis, and diagnosis is improved
Efficiency.
Step S40 searches corresponding historical diagnostic result information according to the label information, is believed according to historical diagnostic result
Breath verifies the targeted diagnostics result.
Believe it should be noted that also historical diagnostic result corresponding with the label information can be searched by label information
Breath, for example, had backed up the historical diagnostic information before user in system, can be traced into from the label information of user user it
Preceding diagnostic result verifies current diagnostic result, to improve the accuracy of system verifying.
In the concrete realization, such as user is directed to the corresponding diagnosis that the disease carries out before, can be to the secondary diagnostic message
It carries out backing up to database, the diagnosis when user diagnoses again, before searching in the database from userspersonal information
Information, so that disease tracking can be further on the one hand carried out, the diagnosis knot that on the other hand diagnostic model of big data is obtained
Fruit is verified, and judges the accuracy of the diagnostic model of big data.
The targeted diagnostics result information is shown by step S50 when verification result is matching.
It should be noted that diagnostic result can be obtained by way of printing, can also be led to when getting diagnostic result
It crosses interface to be shown, the present embodiment with no restriction, consequently facilitating user checks diagnostic result, improves user experience to this.
The present embodiment through the above scheme, by terminal device by the spy in the audit report of user and default diagnostic model
Reference breath is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
Further, as shown in figure 3, proposing big data medical information processing method second of the present invention based on first embodiment
Embodiment, in the present embodiment, the step S20 specifically include:
Step S201 extracts the sampling area in the audit report information, and the feature that the sampling area is acquired is believed
Breath generates feature vector by SIFT algorithm.
In the present embodiment, it obtains the sampling area in examining report information first by SIFT algorithm, extracts sample region
Sampled point in domain, and sampled point is combined generation feature vector, to realize the extraction to characteristic information.
Further, before the step S201, the method also includes:
Step S202 obtains reference inspection report information, and the reference inspection report information is carried out format conversion, conversion
For preset format, the preset format carries sampling area.
It should be noted that due in different audit report information the contents of a project it is different, in order to realize to data
Audit report information, in the present embodiment, is converted to unified reporting format, set in the unified reporting format by processing
There are multiple pickup areas, using the pickup area as the pickup area for generating feature vector, different inspections are reported to realize
Information extraction in announcement makes the system adapt to the demand of different diagnostic devices, improves the flexibility of system processing.
Scheme provided in this embodiment carries out information extraction by SIFT algorithm audit report information, and passes through unification
Reporting format formats different audit report information, to realize the processing to different audit reports, improves system
The flexibility of system processing.
Further, as shown in figure 4, proposing big data medical information of the present invention based on the first embodiment or the second embodiment
Processing method 3rd embodiment is illustrated based on first embodiment in the present embodiment, before the step S30, the side
Method further include:
Step S301 obtains the corresponding relationship of the feature vector of big data and the diagnostic result of big data, by the correspondence
The diagnostic model of relationship generation big data.
It should be noted that in the present embodiment, raw diagnostic model is created first, by sampled data to raw diagnostic mould
Type is trained, to make each data information of raw diagnostic model learning, generates the diagnostic model of big data, and pass through
The diagnostic model of the big data handles audit report information, realizes the data analysis of big data.
Further, before the step S40, the method also includes:
Step S401 prestores the relation mapping table of history tab information and corresponding historical diagnostic result information, root
It is executed according to the relation mapping table and corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic knot
Fruit information verifies the targeted diagnostics result.
In the present embodiment, the mapping table of label information and diagnostic result is established, that is, obtains the diagnostic message of user,
The diagnostic message of user is classified according to user and generates information corresponding to the user, thus getting the corresponding label letter of user
After breath, diagnostic message corresponding with user tag information is found automatically, thus realize the personal management to user information,
Be conducive to carry out data analysis.
Further, the step S40, specifically includes:
Step S402 searches corresponding historical diagnostic result information according to the label information, is not searching the history
When diagnostic result information, diagnostic result information corresponding with other matched label informations of described eigenvector is searched to the mesh
Mark diagnostic result is verified.
It should be noted that there is no historical diagnostic result informations under the information of the corresponding user of the label information
When, in this case, the corresponding diagnostic result of the matched characteristic information of other users can be searched according to the characteristic information of user,
This diagnostic result verifies current diagnostic result, to improve the accuracy of diagnostic result.
Further, before the step S10, the method also includes:
Step S101 judges whether the medical information is legal, when the medical information is legal, executes acquisition user's
Medical information.
It is understood that in order to improve the safety of system processes data, in the present embodiment, retrievable medical treatment letter
Breath carries out safety verification, judges whether the medical information is safety, in the case where medical information is safety, then to described
Medical information is handled.
In the concrete realization, whether the format that can determine whether the medical information is preset format, in the medical information
When format and preset format are inconsistent, then show that the medical information is not safe medical information, then without processing, phase
Ying Di then shows that the medical information is the medical information of safety when the format of the medical information is consistent with preset format,
It is handled again, to improve the safety of system processing.
The present embodiment through the above scheme, by terminal device by the spy in the audit report of user and default diagnostic model
Reference breath is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
The present invention further provides a kind of big data medical information processing systems.
It is the functional block diagram of big data medical information processing system first embodiment of the present invention referring to Fig. 5, Fig. 5.
In big data medical information processing system first embodiment of the present invention, the big data medical information processing system packet
It includes:
Acquisition module 10, for acquiring the medical information of user, the medical information includes audit report information and label
Information.
In the present embodiment, it is based on a set of medical diagnosis system, the medical diagnosis system includes each diagnostic device, example
Such as B ultrasound equipment, CT scan (Computed Tomography, CT) equipment etc. may also include other medical treatment and examine
Disconnected equipment, with no restriction to this, in the present system, the Medical Devices are interconnected the present embodiment, can carry out data communication, are cured
Treat equipment by diagnostic message send in terminal process equipment in the present embodiment, the medical information is analyzed and processed.
In the concrete realization, for the ease of the management for medical information, Medical Devices acquisition user diagnostic message it
The diagnostic message is put on to the label of user afterwards, so that the differentiation with other users, can also carry out user by other means
Mark, the present embodiment to this with no restriction.
Extraction module 20 is generated for extracting the characteristic information in the audit report information according to the characteristic information
Feature vector.
In the concrete realization, by acquiring each information point, by each information point composition characteristic vector, firstly, being reported according to checking
The data generation characteristic information for presetting item in information is accused, such as in the ultrasound diagnosis of stomach, stomach and peripheral part are detected
Echo size and shape size, being for echo size therefore can be big by echo for the key reference factor of inspection result
Small data may also include other crucial parameter informations as characteristic information, by the parameter information of acquisition generate feature to
Amount, so as to pass through the key parameter in characteristic vector pickup report information.
Comparison module 30, for by described eigenvector with have big data diagnostic model in characteristic information compare
Compared with determining the corresponding targeted diagnostics result information of described eigenvector according to comparison result.
It should be noted that in the present embodiment, the diagnostic model of the diagnostic model equipped with big data, the big data is set
There are different characteristic information and corresponding diagnostic result, the medical diagnosis on disease information of decades is included substantially, thus to medical diagnosis on disease
Effectively reference frame is provided.
In the concrete realization, feature vector can be put into the big data with diagnostic model in be iterated and match, obtain
To corresponding diagnostic result, to reduce the one-sidedness of personal diagnosis and reduce the error rate of diagnosis, and diagnosis is improved
Efficiency.
Authentication module 40 is examined for searching corresponding historical diagnostic result information according to the label information according to history
Disconnected result information verifies the targeted diagnostics result.
Believe it should be noted that also historical diagnostic result corresponding with the label information can be searched by label information
Breath, for example, had backed up the historical diagnostic information before user in system, can be traced into from the label information of user user it
Preceding diagnostic result verifies current diagnostic result, to improve the accuracy of system verifying.
In the concrete realization, such as user is directed to the corresponding diagnosis that the disease carries out before, can be to the secondary diagnostic message
It carries out backing up to database, the diagnosis when user diagnoses again, before searching in the database from userspersonal information
Information, so that disease tracking can be further on the one hand carried out, the diagnosis knot that on the other hand diagnostic model of big data is obtained
Fruit is verified, and judges the accuracy of the diagnostic model of big data.
Display module 50, for when verification result is matching, the targeted diagnostics result information to be shown.
It should be noted that diagnostic result can be obtained by way of printing, can also be led to when getting diagnostic result
It crosses interface to be shown, the present embodiment with no restriction, consequently facilitating user checks diagnostic result, improves user experience to this.
The present embodiment through the above scheme, by terminal device by the spy in the audit report of user and default diagnostic model
Reference breath is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
In addition, to achieve the above object, the present invention also proposes a kind of terminal device, the terminal device include: memory,
Processor and the big data medical information processing routine that is stored on the memory and can run on the processor, it is described
Big data medical information processing routine is arranged for carrying out the step of big data medical information processing method as described above.
In addition, the embodiment of the present invention also proposes a kind of storage medium, big data medical treatment letter is stored on the storage medium
Processing routine is ceased, following operation is realized when the big data medical information processing routine is executed by processor:
The medical information of user is acquired, the medical information includes audit report information and label information；
The characteristic information in the audit report information is extracted, feature vector is generated according to the characteristic information；
Described eigenvector is compared with characteristic information in the diagnostic model for having big data, it is true according to comparison result
Determine the corresponding targeted diagnostics result information of described eigenvector；
Corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic result information to described
Targeted diagnostics result is verified；
When verification result is matching, the targeted diagnostics result information is shown.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
The sampling area in the audit report information is extracted, the characteristic information that the sampling area acquires is passed through into SIFT
Algorithm generates feature vector.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
Reference inspection report information is obtained, the reference inspection report information is subjected to format conversion, is converted to default lattice
Formula, the preset format carry sampling area.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
The corresponding relationship for obtaining the feature vector of big data and the diagnostic result of big data generates the corresponding relationship big
The diagnostic model of data.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
The relation mapping table for prestoring history tab information and corresponding historical diagnostic result information, according to the relationship
Mapping table, which is executed, searches corresponding historical diagnostic result information according to the label information, according to historical diagnostic result information to institute
Targeted diagnostics result is stated to be verified.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
Corresponding historical diagnostic result information is searched according to the label information, is not searching the historical diagnostic result letter
When breath, diagnostic result information corresponding with other matched label informations of described eigenvector is searched to the targeted diagnostics result
It is verified.
Further, following operation is also realized when the big data medical information processing routine is executed by processor:
Judge whether the medical information is legal, when the medical information is legal, executes the medical information of acquisition user.
The present embodiment through the above scheme, by terminal device by the spy in the audit report of user and default diagnostic model
Reference breath is compared, and determines the diagnostic result of user, so that the diagnosis by automation improves diagnosis efficiency.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In computer readable storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that an intelligent terminal (can
To be mobile phone, computer, terminal device, air conditioner or the network equipment etc.) execute side described in each embodiment of the present invention
Method.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of big data medical information processing method, which is characterized in that the big data medical information processing method includes:
The medical information of user is acquired, the medical information includes audit report information and label information；
The characteristic information in the audit report information is extracted, feature vector is generated according to the characteristic information；
Described eigenvector is compared with characteristic information in the diagnostic model for having big data, institute is determined according to comparison result
State the corresponding targeted diagnostics result information of feature vector；
Corresponding historical diagnostic result information is searched according to the label information, according to historical diagnostic result information to the target
Diagnostic result is verified；
When verification result is matching, the targeted diagnostics result information is shown.
2. big data medical information processing method as described in claim 1, which is characterized in that described to extract the audit report
Characteristic information in information generates feature vector according to the characteristic information, specifically includes:
The sampling area in the audit report information is extracted, the characteristic information that the sampling area is acquired passes through SIFT algorithm
Generate feature vector.
3. big data medical information processing method as claimed in claim 2, which is characterized in that described to extract the audit report
Sampling area in information, before the characteristic information that the sampling area is acquired generates feature vector by SIFT algorithm, institute
State method further include:
Reference inspection report information is obtained, the reference inspection report information is subjected to format conversion, is converted to preset format, institute
It states preset format and carries sampling area.
4. big data medical information processing method as claimed any one in claims 1 to 3, which is characterized in that described by institute
Feature vector is stated to be compared with characteristic information in the diagnostic model for having big data, according to comparison result determine the feature to
Before measuring corresponding targeted diagnostics result information, the method also includes:
The corresponding relationship is generated big data by the corresponding relationship for obtaining the feature vector of big data and the diagnostic result of big data
Diagnostic model.
5. big data medical information processing method as claimed any one in claims 1 to 3, which is characterized in that the basis
The label information searches corresponding historical diagnostic result information, according to historical diagnostic result information to the targeted diagnostics result
Before being verified, the method also includes:
The relation mapping table for prestoring history tab information and corresponding historical diagnostic result information, according to the relationship map
Table, which is executed, searches corresponding historical diagnostic result information according to the label information, according to historical diagnostic result information to the mesh
Mark diagnostic result is verified.
6. big data medical information processing method as claimed any one in claims 1 to 3, which is characterized in that the basis
The label information searches corresponding historical diagnostic result information, according to historical diagnostic result information to the targeted diagnostics result
It is verified, is specifically included:
Corresponding historical diagnostic result information is searched according to the label information, is not searching the historical diagnostic result information
When, search corresponding with other matched label informations of described eigenvector diagnostic result information to the targeted diagnostics result into
Row verifying.
7. big data medical information processing method as claimed any one in claims 1 to 3, which is characterized in that the acquisition
Before the medical information of user, the method also includes:
Judge whether the medical information is legal, when the medical information is legal, executes the medical information of acquisition user.
8. a kind of big data medical information processing system, which is characterized in that the big data medical information processing system includes:
Acquisition module, for acquiring the medical information of user, the medical information includes audit report information and label information；
Extraction module, for extracting the characteristic information in the audit report information, according to the characteristic information generate feature to
Amount；
Comparison module, for described eigenvector to be compared with characteristic information in the diagnostic model for having big data, according to
Comparison result determines the corresponding targeted diagnostics result information of described eigenvector；
Authentication module, for searching corresponding historical diagnostic result information according to the label information, according to historical diagnostic result
Information verifies the targeted diagnostics result；
Display module, for when verification result is matching, the targeted diagnostics result information to be shown.
9. a kind of terminal device, which is characterized in that the terminal device includes: memory, processor and is stored in the storage
On device and the big data medical information processing routine that can run on the processor, the big data medical information processing routine
The step of big data medical information processing method being arranged for carrying out as described in any one of claims 1 to 7.
10. a kind of storage medium, which is characterized in that be stored with big data medical information processing routine, institute on the storage medium
State the big data realized as described in any one of claims 1 to 7 when big data medical information processing routine is executed by processor
The step of medical information processing method.
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