CN110827991A

CN110827991A - Disease identification data processing method, device, storage medium and electronic equipment

Info

Publication number: CN110827991A
Application number: CN201911065099.2A
Authority: CN
Inventors: 王俊芳; 汤晋军; 王雪莲
Original assignee: Taikang Insurance Group Co Ltd; Taikang Pension Insurance Co Ltd
Current assignee: Taikang Insurance Group Co Ltd; Taikang Pension Insurance Co Ltd
Priority date: 2019-11-04
Filing date: 2019-11-04
Publication date: 2020-02-21

Abstract

The disclosure relates to the technical field of data processing, and provides a disease identification data processing method and device, a computer storage medium and an electronic device, wherein the disease identification data processing method comprises the following steps: receiving an identification request, and acquiring identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request; obtaining authentication rule information according to the authentication application information and the area identification corresponding to the authentication request; and comparing the identification rule information with the identification application information to finish the identification of the diseases to be identified in the identification request according to the comparison result. The technical scheme is favorable for improving the intelligent degree of total disease identification in different regions and improving the disease identification normalization and the disease identification efficiency. Meanwhile, the method avoids the participation of appraisers in the process of disease appraisal, thereby avoiding the defects of low disease appraisal efficiency and low accuracy caused by artificial reasons, and also saving the manpower and material resources required by the disease appraisal.

Description

Disease identification data processing method, device, storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to a disease identification data processing method, a disease identification data processing apparatus, a computer storage medium, and an electronic device.

Background

The identification of the disease refers to examining the condition of the patient to determine whether the patient meets the standard of the corresponding disease. For example, to identify whether a patient has obstructive pulmonary disease, the current patient's condition is identified as meeting the criteria for obstructive pulmonary disease. The description will be given by taking the case of a method of chronic qualification (i.e., qualification for outpatient chronic diseases).

With regard to the determination of the chronic disease qualification, when the determination of the chronic disease qualification is performed in the related art, the related person determines whether the patient is qualified for a treatment for the chronic disease by looking at data such as the results of some examination tests of the patient. The identification result obtained by identifying the outpatient qualification in a manual review mode is easily influenced by subjective factors of related identification personnel, so that the identification result is inaccurate.

The disease identification data processing method provided by the related art is low in normative and low in identification efficiency through a manual review mode, and therefore a solution for automatically processing the patient disease, particularly the chronic disease examination result data, is lacked in the prior art.

It is to be noted that the information disclosed in the background section above is only used to enhance understanding of the background of the present disclosure.

Disclosure of Invention

The present disclosure provides a disease identification data processing method, a disease identification data processing apparatus, a computer storage medium, and an electronic device, and particularly provides a solution for automatically processing patient disease, especially chronic disease examination result data, so as to improve the data processing efficiency of disease identification at least to a certain extent.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.

According to a first aspect of the present disclosure, there is provided a disease identification data processing method comprising:

receiving an identification request, and acquiring identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request;

obtaining authentication rule information according to the authentication application information and the area identification corresponding to the authentication request;

and comparing the identification rule information with the identification application information to finish the identification of the diseases to be identified in the identification request according to the comparison result.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the receiving an identification request, and obtaining identification application information corresponding to a type of a disease to be identified according to the type of the disease to be identified in the identification request includes:

determining a disease identification index according to the type of the disease to be identified in the identification request, and receiving the state information of the user about the disease identification index as an index value of the disease identification index to obtain identification application information corresponding to the type of the disease to be identified.

In an exemplary embodiment of the present disclosure, based on the foregoing solution, the obtaining authentication rule information according to the authentication application information and the area identifier corresponding to the authentication request includes:

and acquiring an authentication rule corresponding to the region identifier and a disease identification index in the authentication application information according to the region identifier in the authentication request, and determining the authentication rule information according to the authentication rule.

In the exemplary embodiment of the present disclosure, based on the foregoing,

the comparing the identification rule information with the identification application information includes:

determining whether the user's condition information regarding the disorder qualification indicator satisfies the qualification rules;

the identification of the disease to be identified is completed according to the comparison result, and comprises the following steps:

and if the condition information of the user about the disease identification index meets the identification details, the disease to be identified passes the identification, and if the condition information of the user about the disease identification index does not meet the identification details, the disease to be identified does not pass the identification.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the authentication rule information includes a plurality of authentication rules; wherein,

querying medical data according to the type of the disease to be identified to determine whether the plurality of identification rules satisfy identification requirements for the disease to be identified;

and if the plurality of identification details meet the identification requirements of the diseases to be identified, comparing the identification rule information with the identification application information.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the method further includes:

and if the plurality of identification details do not meet the identification requirements of the diseases to be identified, reconfiguring identification rule information according to the identification application information.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the querying the medical data according to the type of the disease to be identified to determine whether the plurality of identification rules satisfy the identification requirement for the disease to be identified includes:

querying medical data according to the type of the disease to be identified to determine a target identification rule for identifying the disease to be identified;

and judging whether the identification rule meets the requirement of the target identification rule.

According to a second aspect of the present disclosure, there is provided a disease identification data processing apparatus, the apparatus comprising:

the identification application information acquisition unit is used for receiving an identification request and acquiring identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request;

the authentication rule information configuration unit is used for acquiring authentication rule information according to the authentication application information and the area identifier corresponding to the authentication request;

and the identification unit is used for comparing the identification rule information with the identification application information so as to finish the identification of the diseases to be identified in the identification request according to the comparison result.

According to a third aspect of the present disclosure, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the disease identification data processing method of the first aspect described above.

According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the disease identification data processing method of the first aspect described above via execution of the executable instructions.

As can be seen from the above technical solutions, the disease identification data processing method, the disease identification data processing apparatus, the computer storage medium and the electronic device in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

in some embodiments of the present disclosure, an identification request is received, identification application information corresponding to a type of a disease to be identified is obtained according to the type of the disease to be identified in the identification request, identification rule information is configured according to the identification application information, and further, the identification rule information and the identification application information are compared to complete identification of the disease to be identified according to a comparison result. The identification rules of different regions aiming at the same disease are not completely the same in reality, the complexity of disease identification is increased, and the technical scheme particularly provides a solution for the automatic identification processing of the disease (especially chronic disease) examination result data of patients in different regions. The intelligent degree of disease identification in different regions is improved through a man-machine interaction mode, and the disease identification normalization and the disease identification efficiency are improved. Meanwhile, the method avoids the participation of appraisers in the process of disease appraisal, thereby avoiding the defects of low disease appraisal efficiency and low accuracy caused by artificial reasons, and also saving the manpower and material resources required by the disease appraisal.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.

FIG. 1 shows a schematic flow diagram of a disease identification data processing method in an exemplary embodiment of the present disclosure;

FIG. 2 shows a schematic flow diagram of a disease identification data processing method in another exemplary embodiment of the present disclosure;

FIG. 3 shows a schematic flow diagram of a disease identification data processing method in yet another exemplary embodiment of the present disclosure;

FIG. 4 shows a schematic diagram of a disease identification engine in an exemplary embodiment of the present disclosure;

FIG. 5 shows a schematic flow diagram of a disease identification data processing method in another exemplary embodiment of the present disclosure;

FIG. 6 is a flow chart illustrating a method for determining a disease identification rule according to an exemplary embodiment of the present disclosure;

FIG. 7 shows a schematic flow chart of a disease identification data processing method in an exemplary embodiment of the present disclosure;

fig. 8 shows a schematic configuration diagram of a disease identification data processing apparatus in an exemplary embodiment of the present disclosure;

FIG. 9 shows a schematic diagram of a structure of a computer storage medium in an exemplary embodiment of the disclosure; and

fig. 10 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

The terms "a," "an," "the," and "said" are used in this specification to denote the presence of one or more elements/components/parts/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.; the terms "first" and "second", etc. are used merely as labels, and are not limiting on the number of their objects.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.

In the embodiment of the disclosure, firstly, a disease identification data processing method is provided, which overcomes the defect that the disease identification data processing method provided in the prior art cannot meet the personalized navigation requirement of the user at least to some extent.

Fig. 1 shows a flow chart of a disease identification data processing method in an exemplary embodiment of the present disclosure, and an execution subject of the disease identification data processing method may be a device having a calculation processing function, such as a server or the like.

Referring to fig. 1, a disease identification data processing method according to one embodiment of the present disclosure includes the steps of:

step S110, receiving an identification request, and acquiring identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request;

step S120, obtaining authentication rule information according to the authentication application information and the area identification corresponding to the authentication request; and

and S130, comparing the identification rule information with the identification application information to complete identification of the disease to be identified in the identification request according to a comparison result.

In the technical solution provided in the embodiment shown in fig. 1, an identification request is received, identification application information corresponding to the type of a disease to be identified is obtained according to the type of the disease to be identified in the identification request, identification rule information is configured according to the identification application information, and further, the identification rule information and the identification application information are compared to complete identification of the disease to be identified according to a comparison result. The identification rules of different regions aiming at the same disease are not completely the same in reality, the complexity of disease identification is increased, and the technical scheme particularly provides a solution for the automatic identification processing of the disease (especially chronic disease) examination result data of patients in different regions. The intelligent degree of disease identification in different regions is improved through a man-machine interaction mode, and the disease identification normalization and the disease identification efficiency are improved. Meanwhile, the method avoids the participation of appraisers in the process of disease appraisal, thereby avoiding the defects of low disease appraisal efficiency and low accuracy caused by artificial reasons, and also saving the manpower and material resources required by the disease appraisal.

The following detailed description of the various steps in the example shown in fig. 1:

in an exemplary embodiment, the type of the disease to be identified may be a disease that the user needs to identify, such as obstructive pulmonary disease, chronic pulmonary heart disease, or hypothyroidism. Meanwhile, different disease species correspond to different disease identification indexes. Correspondingly, the above identification application information is the patient condition of the disease identification index corresponding to the disease species. The present embodiment specifically identifies whether the patient is qualified for the corresponding disease category by the condition of the patient.

In step S110, an identification request is received, and identification application information corresponding to the type of the disease to be identified is obtained according to the type of the disease to be identified in the identification request.

In an exemplary embodiment, since the identification rules for the same disease are not exactly the same between different regions, a region identifier should be included in the identification request to clarify the identification rule to which the disease to be identified applies by the region identifier. For example, if a patient in Qingdao intends to identify an obstructive pulmonary disease application he has, the identification request should indicate that the region is identified as Qingdao; for another example, if a patient with carriagnomia is to be asked for identification of an obstructive pulmonary disease, the request for identification should be marked with a local identifier of carriagnomia. Specifically, the region identifier in the above-mentioned identification request is specifically used for determining an embodiment of an identification rule corresponding to the disease to be identified (e.g., an embodiment corresponding to step S120/step S220).

In an exemplary embodiment, fig. 2 shows a flow chart of a disease identification data processing method in another exemplary embodiment of the present disclosure, and referring to fig. 2, the embodiment provides a method including steps S210 to S250. In step S210, as a technical feature of "obtaining identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request" in step S110, a specific embodiment may be provided.

In step S210, a disease identification index is determined according to the type of the disease to be identified in the identification request, and the condition information of the user about the disease identification index is received as an index value of the disease identification index, so as to obtain identification application information corresponding to the type of the disease to be identified.

In an exemplary embodiment, if the type of the disease to be identified in the above-mentioned identification request is chronic obstructive pulmonary disease, a disorder identification index of chronic obstructive pulmonary disease is acquired, and further, condition information of the patient on the above-mentioned disorder identification index is acquired. For example, the condition information may be used as an index value of the disease identification index to obtain identification application information corresponding to the type of the disease to be identified (e.g., chronic obstructive pulmonary disease).

For example, each type of disease may be associated with its corresponding disease identification in advance and stored in a database. Thus, the corresponding disease identification index can be quickly determined according to the type of the disease.

For example, the disease identification index of chronic obstructive pulmonary disease may include: the first disease identification index is that whether the patient has the medical history of chronic bronchitis, emphysema, bronchial asthma and the like; the second disease identification index, the volume value of residual qi of the patient and the like. Further, according to a disease identification index regarding chronic obstructive pulmonary disease, the user inputs patient condition information to the corresponding disease identification index. Thus, the system acquires identification application information on chronic obstructive pulmonary disease. Such as: patient condition with respect to disorder identification index one: the patients have the medical history of chronic bronchitis, emphysema, bronchial asthma and the like; patient condition with respect to disorder identification index two: the patient's residual gas volume value is 30%, etc.

In an exemplary embodiment, the above relationship between chronic obstructive pulmonary disease and its condition indicators is as follows:

"identification index of disease condition one:

the history of chronic bronchitis, emphysema and other pneumothorax diseases or pulmonary vascular diseases is recorded in medical records

Yes/no

And II, identification indexes of diseases:

whether or not there is a pulmonary function test yes/no

And the third disease identification index:

① residual air volume/total lung volume (RV/TLC): ___%

② forced expiratory volume/forced vital capacity in the first second (FEV 1/FVC): (___)%) "

Wherein, the user can reply 'yes' or 'no' to the first disease identification index and the second disease identification index according to the state of the patient; inputting data corresponding to each item in the third disease identification index.

In another exemplary embodiment, the above correlation between thyroid function markers and their disease identification indicators is determined as follows:

"identification index of disease condition one:

the doctor visit record of the nearly three-month clinic is yes/no

And II, identification indexes of diseases:

① thyroid function

② Thyroid Stimulating Hormone (TSH) (___) u IU/L

③ free triiodothyronine (FT3) (___) pmol/L

④ free thyroxine (FT4) (___) pmol/L "

Wherein, the user can reply 'yes' or 'no' to the first disease identification index according to the state of illness of the patient; inputting data corresponding to each item in the second disease identification index.

In step S120, authentication rule information is obtained according to the authentication application information and the area identifier corresponding to the authentication request.

In an exemplary embodiment, step S220 may be implemented as a specific implementation of step S120. Specifically, in step S220, according to the region identifier in the identification request, the identification rule corresponding to the region identifier and the disease identification index in the identification application information is obtained, and the identification rule information is determined according to the identification rule.

For example, the identification details correspond to not only the disease identification index but also the region identifier in the identification request, so as to accurately identify the identification application information determined in the step S110/step 210. In this embodiment, the range of the identification rule is effectively narrowed based on the region identifier in the identification request, and meanwhile, an accurate identification rule is provided for the identification application information, which is beneficial to reducing the complexity of disease identification, and is further beneficial to improving the identification efficiency and the identification accuracy of disease identification.

Illustratively, the identification rule information includes one or more identification rules regarding the same disease type in the same region. For example: for chronic obstructive pulmonary disease, the first disease identification index acquired in step S210: "whether the patient has a history of chronic bronchitis, emphysema, bronchial asthma, etc." the corresponding detailed identification is: "the patient has history of chronic bronchitis, emphysema, bronchial asthma, etc. The second disease identification index acquired in step S210: "what the residual gas volume value of the patient is", the corresponding identification rule is: "the patient's residual gas volume value is greater than 35%".

In an exemplary embodiment, the rules formulated for chronic obstructive pulmonary disease based on medical data or related departments are as follows:

the patients with the medical history of chronic bronchitis, emphysema, bronchial asthma and the like who are hospitalized in more than two levels of hospitals and simultaneously meet the following conditions:

1. frequent cough and expectoration, shortness of breath during early labor, fatigue and loss of labor force as the condition progresses and aggravates.

2. Typical patients have a barrel chest, impaired breathing and movement, epilepsy, impaired speech, increased pulmonary reverberation, downward movement of the turbid lung boundary, reduced heart-sound boundary, impaired breathing sound, and prolonged expiration.

3. Chest X-ray examination has the effects of lung field transmittance enhancement, pulmonary peripheral blood vessel reduction and thinning, diaphragm muscle reduction and flattening, mobility reduction, vertical and long heart shadow or pulmonary bullae.

4. The lung function examination shows that the residual air volume/the total lung volume is more than 35 percent, the forced respiration volume/forced vital capacity in the first second is less than 60 percent, and the maximum ventilation accounts for less than 80 percent of the expected value. "

The rules for chronic obstructive pulmonary disease as described above identify details about this disease as follows:

"identification rule one:

the history of chronic bronchitis, emphysema and other pneumothorax diseases or pulmonary vascular diseases recorded in the medical record is

And II, identifying a rule II:

whether there is a lung function test is

And (3) identifying the third case:

① residual air volume/total lung volume (RV/TLC): (y1) % judgment value:>35％

② forced expiratory volume/forced vital capacity in the first second (FEV1/FVC) ((F))y2) % judgment value:<60％

and selecting 'yes' at the same time for the first and second identification rules, wherein two values in the index three are within a threshold value, and the initial screening is passed. "

Wherein y1 and y2 belong to identification application information, are patient conditions input by a user, and are used for comparison with corresponding judgment values.

In another exemplary embodiment, the determination method of the identification rule of the disease may be determined based on the medical data or the criteria made by the relevant department for the disease. Illustratively, the rules established for thyroid function identification based on medical data or related departments are as follows:

"there are three months of clinic records, and the record conforms to the following 2 items:

1. the clinical manifestations are as follows: there is a low basal metabolic syndrome group: fatigue, bradykinesia, lethargy, edema, etc.;

2. thyroid dysfunction: serum TSH (thyroid stimulating hormone) can be elevated, and FT3 and FT4 are low (TSH > 4.8uIU/L, FT4 < 9pmol/L, FT3 < 3 pmol/L). "

The detailed identification of the disease is determined according to the above rules for thyroid function identification, as follows:

"identification rule one:

the clinic history of the three months is

And II, identifying a rule II:

① thyroid function

② Thyroid Stimulating Hormone (TSH) ((TSH))x1) u IU/L judgment value:>4.8u IU/L

③ free triiodothyronine (FT3) ((R))x2) pmol/L judgement:<3pmol/L

④ free thyroxine (FT4) ((R))x3) pmol/L judgement:<9pmol/L

the first choice of the identification details is "yes", and both of the identification details are within the threshold value, and the identification passes. "

Wherein, the above x1, x2 and x3 belong to the identification application information, are the patient condition inputted by the user, and are used for comparing with the corresponding judgment value.

In step S130, the identification rule information and the identification application information are compared to complete identification of the disease to be identified in the identification request according to the comparison result.

In an exemplary embodiment, steps S230 to S250 may be taken as a specific implementation of step S130. Specifically, in step S230, it is determined whether the condition information of the user about the disorder identification index satisfies the identification rule.

Illustratively, the patient condition for disorder identification index one is: the patients have the medical history of chronic bronchitis, emphysema, bronchial asthma and the like. Correspondingly, the identification details of the first disease identification index are as follows: the patients have the medical history of chronic bronchitis, emphysema, bronchial asthma and the like. The condition of the patient is determined by judgment to meet the first rule of identification on chronic obstructive pulmonary disease.

Illustratively, the patient's condition for disorder identification index two: the patient's residual gas volume value was 30%. Correspondingly, the identification rule of the second disease identification index is as follows: the volume of the patient's residual gas is greater than 35%. And determining that the condition of the patient does not meet the identification rule II about the chronic obstructive pulmonary disease by judgment.

In an exemplary embodiment, if the condition information of the user about the disease identification index satisfies the identification details, indicating that the user satisfies the identification rule of the corresponding disease category, step S240 is performed: the disease to be identified is identified. If the condition information of the user about the disease identification index does not satisfy the identification details, indicating that the user does not satisfy the identification rule of the corresponding disease category, executing step S250: the disease to be identified is not identified.

In an exemplary embodiment, fig. 3 shows a flow chart of a disease identification data processing method in still another exemplary embodiment of the present disclosure, and referring to fig. 3, the method provided by this embodiment includes steps S310 to S340.

The specific implementation of step S310 is the same as the specific implementation of step S110, and the specific implementation of step S320 is the same as the specific implementation of step S120, which are not described herein again.

In step S330, medical data is queried according to the type of the disease to be identified to determine whether the plurality of identification rules satisfy the identification requirement for the disease to be identified.

Illustratively, in order to improve the accuracy of disease identification, the technical solution provided in this embodiment audits the identification rules. Specifically, the medical data may be queried according to the type of the disease to be identified to determine a target identification rule for identifying the disease to be identified; and further judging whether the identification rule meets the requirement of the target identification rule.

For example, the identification rule information that the system determines about disease a includes: identification rule a, identification rule b and identification rule c. The determination of the identification rule information about the disease a according to the query medical data or according to the rules established by the relevant departments includes: target identification rule a, target identification rule b', target identification rule c. As can be seen, the identification rule is updated, which indicates that the identification rule determined by the system for disease a does not satisfy the identification requirement for the disease to be identified, and then step S320 is executed again: and ranking the authentication application information to authentication rule information according to the authentication application information so as to update the authentication rule b to the target authentication rule b'.

In an exemplary embodiment, if the plurality of identification details satisfy the identification requirement for the disease to be identified, step S340 is performed: and comparing the identification rule information with the identification application information to finish the identification of the diseases to be identified in the identification request according to the comparison result.

The specific implementation of step S340 is the same as the specific implementation of step S130, and is not described herein again.

The following examples will illustrate the technical solutions of the present disclosure, taking the qualification of chronic (outpatient chronic disease) as an example.

Fig. 4 is a schematic structural diagram of a portal chronic qualification engine according to an embodiment of the disclosure, and fig. 5 is a schematic structural diagram of a process for performing qualification of an outpatient chronic disease based on the portal chronic qualification. Specifically, referring to fig. 4 and 5, the method for identifying chronic status of an outpatient clinic according to the embodiment is as follows:

in step S51, a disease species to be identified is selected. Illustratively, the disease category acquisition module provides an identification of a plurality of disease category names or disease types for selection by the user. Alternatively, the user may also directly enter an identification of the disease species or disease type to be identified. Illustratively, the seed acquisition module provides a plurality of region identifiers for selection by the user. Thus, the type of the disease to be identified and the region identification selected/input by the user are taken as the above-mentioned identification request, and sent to the chronic disease application data template module 401 of the gate chronic qualification engine 400.

In step S52, the chronic disease application data template module 401 of the gate chronic qualification engine 400 returns an application data template related to the disease to be qualified according to the received qualification request. Illustratively, the application data template includes a disease identification index for a disease species to be identified and a corresponding data item (i.e., identification application information) to obtain a patient condition. For example, the user may enter the patient condition information according to the disease identification index in the template, thereby determining the disease identification application information.

In step S53, the identification rule configuration module 402 of the slow qualification engine 400 configures the identification rule of the disease to be qualified according to the region identifier in the identification request and the disease identification index of the disease to be qualified. For example, the identification rule includes a plurality of identification rules, and the identification rule corresponds to the disease identification index and is a standard for identifying the identification application information.

In step S54, the authentication rule checking module 403 of the gate slow qualification engine 400 checks the authentication rule determined in step S53. Illustratively, the latest data corresponding to the region identifier and the disease to be identified is obtained from the database 405(DB/FILE) (for example, the database 405 is updated with regular/irregular data), and the target identification rule is checked according to the target identification rule and the identification rule determined in step S53. If the verification result is that the authentication rule is correct, the verification result is stored but does not take effect. And if the checking result is that a problem possibly exists, sending out prompt information to prompt a user to modify the determined authentication rule.

In step S55, the authentication rule checking module 403 of the gate slow qualification engine 400 returns the result of the checking with respect to the embodiment of step S54. And if the checking result shows that the current identification rule can not meet the identification requirement of the disease species, executing the steps S56-S59. If the checking result is that the current identification rule can meet the identification requirement of the disease species, directly executing step S58 and step S59.

In step S56, the identification rule for identifying the corresponding disease category to be identified in the area is reloaded. The embodiment is the same as step S53.

In step S57, the reload result is returned. The embodiment is the same as step S54.

In step S58, the identification execution module 404 of the gate-slow qualification engine 400 executes the disease identification according to the determined identification rule corresponding to the region identifier and corresponding to the disease to be identified. Illustratively, the authentication rule information and the authentication application information are compared. More specifically, it is determined whether the condition information of the user about the disorder identification index satisfies the identification rule.

In step S59, the identification execution module 404 of the gate slow qualification engine 400 returns the disease identification result. Illustratively, the disease to be identified is identified by the identification if the condition information of the user about the disorder identification index satisfies the identification details, and the disease to be identified is not identified by the identification if the condition information of the user about the disorder identification index does not satisfy the identification details.

In the technical solution provided in the embodiment shown in fig. 5, identification application information is obtained according to the disease species of the chronic disease to be identified, identification rule information is configured according to the identification application information, and further, the identification rule information and the identification application information are compared to complete identification of the disease to be identified according to the comparison result. According to the technical scheme, the intelligent degree of identifying the slow diseases in different regions is improved in a man-machine interaction mode, and the standardization of identifying the slow diseases and the efficiency of identifying the diseases are improved. Meanwhile, the method avoids the identification personnel from participating in the process of disease identification, thereby avoiding the defects of low efficiency and low accuracy of identifying the chronic diseases caused by human factors and saving the manpower and material resources required by identifying the chronic diseases.

Fig. 6 is a flow chart illustrating a method for determining a disease identification rule according to an exemplary embodiment of the disclosure. In particular, FIG. 6 provides a method for determining the identification rules of a portal disease. Referring to fig. 6, the method provided by this embodiment includes steps S610 to S660.

In step S610, chronic obstructive pulmonary disease is selected.

Illustratively, the system provides a plurality of identifications of disease names or disease types for the pre-determined disease for selection by the user. In addition, the user can also directly input a name of a disease or an identification of a type of disease that is a chronic disease. In this embodiment, the user selects chronic obstructive pulmonary disease as the disease to be identified.

In step S620, a chronic obstructive pulmonary disease identification rule is configured based on the identification application information of chronic obstructive pulmonary disease.

Exemplary information on the application for identifying chronic obstructive pulmonary disease includes: chronic obstructive pulmonary disease, and a patient condition entered by a user with respect to each disorder index.

Illustratively, identification rules corresponding to the disease identification indexes in the above identification application information are obtained, wherein the identification rules determine the chronic obstructive pulmonary disease.

In step S630, it is determined whether the currently configured chronic obstructive pulmonary disease identification rule is reasonable.

For example, it may be determined whether the currently configured qualification rules comply with medical logic, etc.

Illustratively, if it is reasonable, step S640 is executed; if not, the process returns to step S620.

In step S640, the currently configured identification rule of chronic obstructive pulmonary disease is checked.

In step S650, it is determined whether the chronic obstructive pulmonary disease identification rule is correct.

For example, if the result is correct, step S660 is executed; if not, the process returns to step S620.

In step S660, the lentigo qualification rules are validated.

Fig. 7 shows a schematic flow chart of a disease identification data processing method in an exemplary embodiment of the present disclosure. In particular, fig. 7 provides a user application for an identification procedure for chronic obstructive pulmonary disease. Referring to fig. 7, the method provided by this embodiment includes steps S710 to S750.

In step S710, identification application information for chronic obstructive pulmonary disease is entered.

Illustratively, each type of disease is pre-associated with its corresponding disease identification index and stored in a database. Thus, the corresponding disease identification index can be quickly determined according to the type of the disease. According to the disease identification indexes provided by the system for chronic obstructive pulmonary disease, the user fills out the patient condition about each disease identification index.

In step S720, the portal slowness qualification application module of the management platform chronic disease system calls the portal slowness qualification engine.

In step S730, the portal qualification engine acquires a qualification rule for chronic obstructive pulmonary disease from the disease species.

Illustratively, identification rules corresponding to the disease identification index of the chronic obstructive pulmonary disease are obtained, wherein the identification rules are determined by the identification rules.

In step S740, the gate slow qualification engine gives a preliminary screening result according to the qualification rule and the application data of the copd and informs the management platform. And, in step S750, the management platform displays the result of the slow qualification engine for future acceptance, review and audit.

Those skilled in the art will appreciate that all or part of the steps implementing the above embodiments are implemented as computer programs executed by a CPU. The computer program, when executed by the CPU, performs the functions defined by the method provided by the present invention. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic or optical disk, or the like.

Furthermore, it should be noted that the above-mentioned figures are only schematic illustrations of the processes involved in the method according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

The following describes an embodiment of an apparatus of the present disclosure, which may be used to perform the method for recommending a driving route of the present disclosure.

Fig. 8 shows a schematic configuration diagram of a disease identification data processing apparatus in an exemplary embodiment of the present disclosure. As shown in fig. 8, the disease identification data processing device 800 includes: an authentication application information acquisition unit 801, an authentication rule information configuration unit 802, and an authentication unit 803.

Wherein: an identification application information obtaining unit 801 configured to receive an identification request, and obtain identification application information corresponding to a type of a disease to be identified according to the type of the disease to be identified in the identification request;

an authentication rule information configuration unit 802, configured to obtain authentication rule information according to the authentication application information and the area identifier corresponding to the authentication request;

an identifying unit 803, configured to compare the identification rule information with the identification application information, so as to complete identification of the disease to be identified in the identification request according to the comparison result.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the identification application information obtaining unit 801 is specifically configured to:

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the identification rule information configuring unit 802 is specifically configured to:

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the identification unit 803 is specifically configured to:

determining whether the user's condition information regarding the disorder qualification indicator satisfies the qualification rules; and if the condition information of the user on the disease identification index meets the identification details, the disease to be identified passes the identification, and if the condition information of the user on the disease identification index does not meet the identification details, the disease to be identified fails the identification.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, the authentication rule information includes a plurality of authentication rules; wherein the identification unit 803 is specifically configured to:

querying medical data according to the type of the disease to be identified to determine whether the plurality of identification rules satisfy identification requirements for the disease to be identified; and if the plurality of identification details meet the identification requirements for the disease to be identified, comparing the identification rule information with the identification application information.

In an exemplary embodiment of the present disclosure, based on the foregoing scheme, if the plurality of identification details do not satisfy the identification requirement for the disease to be identified, the identification rule information is further used for: and reconfiguring authentication rule information according to the authentication application information.

querying medical data according to the type of the disease to be identified to determine a target identification rule for identifying the disease to be identified; and judging whether the identification rule meets the requirement of the target identification rule.

The specific details of each module in the disease identification data processing device have been described in detail in the corresponding disease identification data processing method, and thus are not described herein again.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to perform the steps according to various exemplary embodiments of the disclosure described in the "exemplary methods" section above of this specification, when the program product is run on the terminal device.

Referring to fig. 9, a program product 900 for implementing the above method according to an embodiment of the present disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.

An electronic device 1000 according to this embodiment of the disclosure is described below with reference to fig. 10. The electronic device 1000 shown in fig. 10 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 10, the electronic device 1000 is embodied in the form of a general purpose computing device. The components of the electronic device 1000 may include, but are not limited to: the at least one processing unit 1010, the at least one memory unit 520, and a bus 1030 that couples various system components including the memory unit 1020 and the processing unit 1010.

Wherein the storage unit stores program code that is executable by the processing unit 1010 to cause the processing unit 1010 to perform steps according to various exemplary embodiments of the present disclosure described in the above section "exemplary methods" of the present specification. For example, the processing unit 1010 may perform the following as shown in fig. 1: step S110, receiving an identification request, and acquiring identification application information corresponding to the type of the disease to be identified according to the type of the disease to be identified in the identification request; step S120, obtaining authentication rule information according to the authentication application information and the area identification corresponding to the authentication request; and step S130, comparing the identification rule information with the identification application information to complete identification of the disease to be identified in the identification request according to the comparison result.

The storage unit 1020 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)10201 and/or a cache memory unit 10202, and may further include a read-only memory unit (ROM) 10203.

The memory unit 1020 may also include a program/utility 10204 having a set (at least one) of program modules 10205, such program modules 10205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 1030 may be any one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, and a local bus using any of a variety of bus architectures.

The electronic device 1000 may also communicate with one or more external devices 1100 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 1000, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 1000 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interfaces 1050. Also, the electronic device 1000 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 1060. As shown, the network adapter 1060 communicates with the other modules of the electronic device 1000 over the bus 1030. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method of disease identification data processing, the method comprising:

2. The disease identification data processing method according to claim 1, wherein the obtaining of identification application information corresponding to the type of the disease to be identified from the type of the disease to be identified in the identification request includes:

3. The disease identification data processing method according to claim 2, wherein the obtaining of identification rule information based on the identification application information and the region identifier corresponding to the identification request includes:

4. The disease identification data processing method according to claim 3,

the identification of the disease to be identified in the identification request is completed according to the comparison result, and comprises the following steps:

5. The disease identification data processing method according to claim 1, wherein the identification rule information includes a plurality of identification rules; wherein,

6. The disease identification data processing method of claim 5, further comprising:

7. The disease identification data processing method according to claim 5 or 6, wherein the querying of the medical data according to the type of the disease to be identified to determine whether the plurality of identification rules satisfy the identification requirement for the disease to be identified comprises:

8. A disease identification data processing apparatus, characterized in that the apparatus comprises:

9. A computer storage medium on which a computer program is stored, the computer program, when being executed by a processor, implementing a disease identification data processing method according to any one of claims 1 to 7.

10. An electronic device, comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the disease identification data processing method of any one of claims 1 to 7 via execution of the executable instructions.