Methods, devices, electronic equipment, and computer media for creating disease-specific databases

Abstract

This disclosure relates to a method, apparatus, electronic device, and computer-readable medium for creating a disease-specific database, belonging to the field of data processing technology. The method includes: acquiring common indicators based on multiple disease-specific data models and generating full-scale indicator data; providing a visual interactive configuration interface on a user interface, and generating a disease-specific data retrieval statement based on disease-specific configuration information selected by the user on the interactive configuration interface; retrieving disease-specific patient data from the full-scale indicator data according to the disease-specific data retrieval statement; generating a disease-specific dataset based on the disease-specific patient data, and creating a corresponding disease-specific database. This disclosure improves the efficiency of disease-specific database creation by extracting and layering common indicators from multiple different disease-specific data models, generating full-scale indicator data, and providing a visual interactive configuration interface. If the user needs to add incremental indicators to a specific disease-specific database, corresponding disease-specific indicator data can also be generated based on the incremental indicators.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of data processing, in particular to a method for creating a disease database, an apparatus for creating a disease database, an electronic device and a computer readable medium. BACKGROUND

[0002] The disease database refers to a disease database for scientific researchers. The disease database is constructed by using the past accumulated electronic clinical data of a hospital to form a high-quality real world database. On the basis of the data, online tools are integrated to carry out scientific research, so as to improve the efficiency of data collection, processing, analysis and the whole process of scientific research.

[0003] However, when multiple disease databases are constructed for multiple departments of a hospital, different indicators / fields need to be structured or logically processed from unstructured text according to different diseases / subjects in each disease database. Therefore, the creation and implementation of each disease database need to go through a long design process, including indicator demand collection, model design, data processing rule configuration, data processing production, data quality testing, function testing, etc. In actual operation, there are a large number of repeated basic indicators between the data models of different diseases / subjects. If data production is performed for each database separately, there is a certain technical threshold, and the efficiency of database creation is low.

[0004] Therefore, there is an urgent need in the art for a method for creating a disease database, which can reduce the technical threshold of creating a disease database and improve the efficiency of creating a disease database.

[0005] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The purpose of the present disclosure is to provide a method for creating a disease database, an apparatus for creating a disease database, an electronic device and a computer readable medium, thereby at least reducing the technical threshold of creating a disease database and improving the efficiency of creating a disease database.

[0007] According to a first aspect of the present disclosure, a method for creating a disease database is provided, comprising:

[0008] obtaining public indicators based on a plurality of disease data models, and producing full-amount indicator data according to the public indicators;

[0009] providing a visual interactive configuration interface on a user interface, and generating a corresponding disease data retrieval statement based on disease configuration information selected by a user on the interactive configuration interface;

[0010] obtaining corresponding special disease patient data from the total amount index data according to the special disease data retrieval statement;

[0011] generating a special disease data set according to the special disease patient data, and creating a corresponding special disease database according to the special disease data set.

[0012] In an exemplary embodiment of the present disclosure, the production of the total amount index data according to the public index comprises:

[0013] obtaining total amount patient data from a plurality of different data sources, and putting the total amount patient data into a total amount preposition database;

[0014] extracting target total amount data from the total amount preposition database according to the public index, and performing structured processing on the target total amount data to obtain structured total amount index data.

[0015] In an exemplary embodiment of the present disclosure, after the special disease database is created, the method further comprises:

[0016] obtaining special disease incremental indexes corresponding to the special disease database, and producing corresponding special disease index data according to the special disease incremental indexes.

[0017] In an exemplary embodiment of the present disclosure, the production of the special disease index data according to the special disease incremental indexes comprises:

[0018] obtaining the special disease patient data from the special disease database, and putting the special disease patient data into an incremental preposition database;

[0019] extracting target incremental data from the incremental preposition database according to the special disease incremental indexes, and performing structured processing on the target incremental data to obtain structured special disease index data.

[0020] In an exemplary embodiment of the present disclosure, the generation of the corresponding special disease data retrieval statement based on the special disease configuration information selected by the user on the interactive configuration interface comprises:

[0021] determining patient data screening rules based on the special disease configuration information selected by the user on the interactive configuration interface, and generating a corresponding special disease data retrieval statement according to the patient data screening rules.

[0022] In an exemplary embodiment of the present disclosure, the determination of the patient data screening rules based on the special disease configuration information selected by the user on the interactive configuration interface comprises:

[0023] The corresponding special disease patient data inclusion rule is determined based on the special disease data inclusion configuration, and the corresponding special disease patient data exclusion rule is determined based on the special disease data exclusion configuration.

[0024] The patient data screening rule is determined according to the special disease patient data inclusion rule and the special disease patient data exclusion rule.

[0025] In an exemplary embodiment of the present disclosure, the special disease patient data set is generated according to the special disease patient data, comprising:

[0026] The special disease database corresponding to the special disease patient data is added to the special disease label, and the special disease data set is generated.

[0027] According to a second aspect of the present disclosure, a special disease database creation device is provided, comprising:

[0028] The full amount data production module is configured to obtain public indicators based on a plurality of special disease data models, and to produce full amount indicator data according to the public indicators;

[0029] The search statement generation module is configured to provide a visual interactive configuration interface on a user interface, and to generate a corresponding special disease data search statement based on special disease configuration information selected by a user on the interactive configuration interface;

[0030] The special disease data acquisition module is configured to acquire corresponding special disease patient data from the full amount indicator data according to the special disease data search statement;

[0031] The special disease database creation module is configured to generate a special disease data set according to the special disease patient data, and to create a corresponding special disease database according to the special disease data set.

[0032] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the above-mentioned special disease database creation method via execution of the executable instructions.

[0033] According to a fourth aspect of the present disclosure, a computer readable medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned special disease database creation method.

[0034] The exemplary embodiments of the present disclosure can have the following beneficial effects:

[0035] In the method for creating a special disease database of the example embodiment of the present disclosure, on one hand, by providing a visual interactive configuration interface and automatically generating a retrieval statement according to the special disease configuration information selected by a user on the interactive configuration interface, the technical threshold for creating a special disease database can be reduced, and the user can independently complete the configuration of the data range without a computer professional background, thereby improving the efficiency and autonomy of the user in creating a special disease database. On the other hand, for the scenario of simultaneously constructing multiple special disease databases, a public index layer is formed by extracting public indexes from multiple different special disease data models. After data access, the full-amount index data corresponding to the public index layer can be uniformly produced for all patients in the hospital, and the corresponding special disease database is created based on the full-amount index data. This not only can reduce the repeated work and the generation of redundant data, reduce unnecessary consumption of storage space, but also can improve the data production efficiency when multiple special disease databases are simultaneously constructed, and greatly reduce the production implementation cost.

[0036] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0037] The drawings incorporated into the specification and forming a part thereof illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0038] Figure 1 A flowchart of the method for creating a special disease database of the example embodiment of the present disclosure is shown;

[0039] Figure 2 A flowchart of the method for creating a special disease database of the example embodiment of the present disclosure is shown;

[0040] Figure 3 A flowchart of the method for creating a special disease database of the example embodiment of the present disclosure is shown;

[0041] Figure 4 An interface display diagram of the interactive configuration interface according to one specific embodiment of the present disclosure is schematically shown;

[0042] Figure 5 A flowchart of the method for creating a special disease database of the example embodiment of the present disclosure is shown;

[0043] Figure 6 A block diagram of the special disease database creation device of the example embodiment of the present disclosure is shown;

[0044] Figure 7 A structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0045] Example embodiments now will be described more fully hereinafter with reference to the accompanying drawings. Example embodiments, however, can be implemented 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 scope of the example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined 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 embodiments of the disclosure can be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures have not been described in detail to avoid obscuring aspects of the subject matter presented in this disclosure.

[0046] Furthermore, the accompanying drawings are only schematic and are non-limiting exact representations of embodiments of the present disclosure. Identical components have been given the same reference numerals in the various drawings and will not be described in detail with reference to the same. Some of the blocks in the drawings are functional blocks that represent functions implemented by software, hardware or a combination of software and hardware. The functional blocks can be implemented in software or hardware or a combination thereof. In some embodiments, the functional blocks can be implemented in one or more hardware modules or integrated circuits.

[0047] The creation of the disease-specific database requires patient data specified by the NCI to be the basis for data processing and production. In some related embodiments, the scope of data production is determined by the research and development personnel translating the NCI conditions provided by medical workers into database retrieval statements, such as SQL (Structured Query Language) retrieval statements, NoSQL (Not Only SQL) retrieval statements, etc., and then querying and extracting the corresponding patient data from the original medical system database through the database retrieval statements. If the query is directly performed in the original database through professional database retrieval statements, there are often cases of inaccurate translation that need to be adjusted repeatedly. The operation has a technical threshold, and is not operable for non-computer professionals. Therefore, it is mainly outsourced by the technical team of a big data company, and the user's autonomy is not strong.

[0048] On the other hand, the data processing production process of each special disease database includes index demand collection, model design, data processing rule configuration, data processing production, data quality testing, function testing and other production processes. For some fields shared by multiple special disease databases, the entire production process needs to be repeated, which not only consumes time and effort, but also causes data redundancy and increases unnecessary consumption of storage space.

[0049] For example, the "positive symptom" index is a shared index, which is included in the "hypertension special disease database" and the "coronary heart disease special disease database". However, the overlap between the hypertension population and the coronary heart disease population is relatively large, so in the above two special disease databases, the index will be produced for the overlapping part of the patients in the two databases respectively, causing data redundancy and repeated human time and cost.

[0050] Based on the above problems, the present example embodiment first provides a special disease database creation method. Referring to Figure 1 The special disease database creation method can include the following steps:

[0051] Step S110. Obtain common indexes based on multiple special disease data models, and produce full-amount index data according to the common indexes.

[0052] Step S120. Provide a visual interactive configuration interface on the user interface, and generate a corresponding special disease data retrieval statement based on the special disease configuration information selected by the user on the interactive configuration interface.

[0053] Step S130. Obtain corresponding special disease patient data from the full-amount index data according to the special disease data retrieval statement.

[0054] Step S140. Generate a special disease data set according to the special disease patient data, and create a corresponding special disease database according to the special disease data set.

[0055] In the method for creating the special disease database of the example embodiment of the present disclosure, on one hand, by providing a visual interactive configuration interface and automatically generating a retrieval statement according to the special disease configuration information selected by the user on the interactive configuration interface, the technical threshold for creating the special disease database can be reduced, and the user can independently complete the configuration of the data range without a computer professional background, thereby improving the efficiency and autonomy of the user in creating the special disease database. On the other hand, for the scenario of simultaneously constructing multiple special disease databases, a public index layer is formed by extracting public indexes from multiple different special disease data models. After data access, the full-volume index data corresponding to the public index layer can be uniformly produced for all patients in the hospital, and the corresponding special disease databases are created based on the full-volume index data. This not only reduces the repeated work and the generation of redundant data, reduces unnecessary consumption of storage space, but also improves the data production efficiency when multiple special disease databases are simultaneously constructed, and greatly reduces the production implementation cost.

[0056] Next, the above steps of the example embodiment will be described in detail. Figures 2 to 5 The above steps of the example embodiment will be described in detail.

[0057] In step S110, the public indexes are obtained based on multiple special disease data models, and the full-volume index data is produced according to the public indexes.

[0058] In the creation of the special disease database, the most time-consuming and labor-intensive is the processing and production of data. Therefore, how to improve the efficiency of data production is the key to improving the experience of the special disease database and the key to optimizing the implementation cost.

[0059] In the example embodiment, an optimization scheme of the data production method is proposed for the scenario of simultaneously constructing multiple special disease databases in a hospital. By layering the existing special disease data models, the public indexes in each special disease data model are extracted as a public index layer of the model. After data access, the full-volume index data corresponding to the public index layer is first produced for all patients in the hospital.

[0060] The public index refers to an index that is not specific to a particular disease / subject, the index processing logic in different models is consistent, and the index is universal.

[0061] For example, the "positive symptom" index is included in the "hypertension special disease database" and the "coronary heart disease special disease database" as a public index. By layering and merging the repeated and combinable tasks in the data production process of multiple special disease databases, the public indexes are extracted from multiple special disease data models, and the full-volume index data is produced according to the public indexes. Multiple different special disease databases are established based on the full-volume index data, which can improve the overall efficiency and reduce the production cost.

[0062] In the example embodiment, as shown in FIG. 13, the full-volume indicator data is produced according to the common indicators, which can include the following steps: Figure 2

[0063] Step S210. Obtain full-volume patient data from multiple different data sources and put the full-volume patient data into a full-volume pre-database.

[0064] Figure 3 A flowchart of the process of producing full-volume indicator data according to one specific embodiment of the present disclosure is schematically shown. When producing data, first, the full-volume patient data to be processed is obtained from multiple heterogeneous data sources, such as HIS (Hospital Information System), LIS (Laboratory Information Management System), and some unstructured data sources, and is put into a full-volume pre-database as backup data for the production of full-volume indicator data after data synchronization.

[0065] Step S220. Extract target full-volume data from the full-volume pre-database according to the common indicators and perform structured processing on the target full-volume data to obtain structured full-volume indicator data.

[0066] After extracting the target full-volume data from the full-volume pre-database according to the common indicators, structured full-volume indicator data can be obtained after data mapping, data cleaning and data parsing, data enhancement, and structured processing. At the same time of data processing, data quality control and difference analysis can be performed to monitor data processing indicators such as data missing rate, so as to ensure the quality of the generated full-volume indicator data.

[0067] On the basis of the full-volume indicator data of the whole hospital, the hospital user can self-help query the patient data meeting the conditions to create a corresponding special disease database.

[0068] In step S120, a visual interactive configuration interface is provided on the user interface, and a corresponding special disease data retrieval statement is generated based on the special disease configuration information selected by the user on the interactive configuration interface.

[0069] In the example embodiment, a visual interactive configuration interface can be provided on the user interface, patient data filtering rules are determined based on the special disease configuration information selected by the user on the interactive configuration interface, and a corresponding special disease data retrieval statement is generated according to the patient data filtering rules.

[0070] ​In determining the patient data screening rule, the corresponding special disease patient data inclusion rule can be determined based on the special disease data inclusion configuration, the corresponding special disease patient data exclusion rule can be determined based on the special disease data exclusion configuration, and then the patient data screening rule can be determined according to the special disease patient data inclusion rule and the special disease patient data exclusion rule. The special disease patient data inclusion rule refers to the data range screening rule included in the special disease patient data to be obtained, for example, the patient data of the coronary heart disease patients over 60 years old is to be obtained. The special disease patient data exclusion rule refers to the data range screening rule that needs to be excluded from the special disease patient data to be obtained, for example, the patient data of patients with hypertension needs to be excluded.

[0071] Figure 4 The interface display diagram of the interactive configuration interface according to one specific embodiment of the present disclosure is schematically shown. In the interactive configuration interface, the inclusion standard selection interface and the exclusion standard selection interface can be included, and the number of inclusions and exclusions corresponding to the conditions can be displayed between each condition selection box.

[0072] The user selects the corresponding screening conditions and sets the value range on the visual interactive configuration interface through the condition tree inclusion and exclusion rule setting, associates the rules through the "and" / "or" logic and the "same medical record" / "same report" / "same patient" logic, and determines the patient data screening rule. Then, through the use of retrieval statement automatic generation technology, after the user completes the configuration of the patient data screening rule independently, the automatic generation of the special disease data retrieval statement is realized.

[0073] In step S130, the corresponding special disease patient data is obtained from the full amount of index data according to the special disease data retrieval statement.

[0074] In the example embodiment, after the special disease data retrieval statement is generated, the corresponding special disease patient data can be obtained from the full amount of index data according to the special disease data retrieval statement, and used as the data basis of the specified special disease database.

[0075] In step S140, the special disease data set is generated according to the special disease patient data, and the corresponding special disease database is created according to the special disease data set.

[0076] In the example embodiment, the special disease patient data can be added with the special disease label corresponding to the special disease database and the special disease data set is generated, and then the corresponding special disease database is created according to the special disease data set.

[0077] In this example implementation, after creating a disease-specific database, if a user needs to add customized processing indicators for a specific disease-specific database, they can obtain the corresponding incremental indicators for that database and generate corresponding disease-specific indicator data based on these incremental indicators. By providing incremental processing indicators for a specific disease-specific database, the production cost of repetitive general indicators can be reduced. Furthermore, in the production of incremental data, only the quality of the incremental data needs to be verified, which also reduces the manpower and time costs of testing.

[0078] In this example implementation, when generating corresponding disease-specific indicator data based on incremental disease indicators, disease-specific patient data can be obtained from the disease-specific database and placed into the incremental pre-database. Then, target incremental data is extracted from the incremental pre-database based on the disease-specific incremental indicators, and the target incremental data is subjected to structured processing to obtain structured disease-specific indicator data. The specific data processing method is as follows... Figure 3 The processing method for full data is similar and will not be elaborated here. Both stages each contain complete data production steps, including data access, data processing, and data application.

[0079] In the production process of disease-specific indicator data, the disease-specific data model can be layered, and customized indicators for non-shared diseases / disciplines can be produced incrementally in stages. This layered and staged data production model reduces the manpower and time costs of producing multiple full-indicator models, thereby significantly shortening the overall data production cycle of the disease-specific database. This further improves data production efficiency when multiple disease-specific databases are being built simultaneously across the hospital, and substantially reduces production implementation costs. Furthermore, reducing intermediate steps in data production can further improve production efficiency.

[0080] like Figure 5 The diagram shown is a complete flowchart of the self-service creation of a disease-specific database in a specific embodiment of this disclosure. It is an example illustration of the above steps in this exemplary embodiment. The specific steps of the flowchart are as follows:

[0081] Step S510. Set the rules for inclusion and exclusion in the condition tree.

[0082] Users can configure the inclusion and exclusion rules by selecting the corresponding filtering conditions and setting the value range through the condition tree inclusion and exclusion rule settings (visual interactive configuration interface). After that, they can associate the rules through "AND" / "OR" logic, as well as logic such as "same medical record" / "same report" / "same patient" to form the inclusion and exclusion rule configuration for the data range.

[0083] Step S520. Search statement is automatically generated.

[0084] The system automatically generates corresponding disease-specific data retrieval statements based on data range filtering rules.

[0085] Step S530. Query target patient data.

[0086] The target patient data is obtained by querying the multi-source database using the generated disease-specific data retrieval statement.

[0087] Step S540. Add labels to patient data.

[0088] The target patient data is labeled with the corresponding disease-specific database to generate a disease-specific data set.

[0089] Step S550. Create a disease-specific database.

[0090] Finally, the disease-specific data set is read to create a specified disease-specific database.

[0091] It should be noted that although the steps of the method in the present disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. In addition or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be divided into multiple steps, etc.

[0092] Further, the present disclosure also provides a disease-specific database creation apparatus. Referring to Figure 6 shown, the disease-specific database creation apparatus can include a full data production module 610, a retrieval statement generation module 620, a disease-specific data acquisition module 630, and a disease-specific database creation module 640. Among them:

[0093] The full data production module 610 can be used to obtain common indicators based on a plurality of disease-specific data models, and to produce full indicator data according to the common indicators;

[0094] The retrieval statement generation module 620 can be used to provide a visual interactive configuration interface on a user interface, and to generate a corresponding disease-specific data retrieval statement based on disease-specific configuration information selected by a user on the interactive configuration interface;

[0095] The disease-specific data acquisition module 630 can be used to acquire corresponding disease-specific patient data from the full indicator data according to the disease-specific data retrieval statement;

[0096] The disease-specific database creation module 640 can be used to generate a disease-specific data set according to the disease-specific patient data, and to create a corresponding disease-specific database according to the disease-specific data set.

[0097] In some exemplary embodiments of the present disclosure, the full data production module 610 can include a full patient data acquisition unit and a full data structuring unit. Among them:

[0098] The full-patient-data acquisition unit can be configured to acquire full-patient data from a plurality of different data sources and place the full-patient data into a full-prefetch database;

[0099] The full-data structuring unit can be configured to extract target full-patient data from the full-prefetch database according to common indicators, and perform structured processing on the target full-patient data to obtain structured full-indicator data.

[0100] In some example embodiments of the present disclosure, the apparatus for creating a disease-specific database provided by the present disclosure can further include a disease-specific indicator data production module, which can be configured to acquire disease-specific incremental indicators corresponding to the disease-specific database, and produce disease-specific indicator data corresponding to the disease-specific incremental indicators.

[0101] In some example embodiments of the present disclosure, the disease-specific indicator data production module can include a disease-specific patient data acquisition unit and an incremental data structuring unit. Wherein:

[0102] The disease-specific patient data acquisition unit can be configured to acquire disease-specific patient data from the disease-specific database and place the disease-specific patient data into an incremental-prefetch database;

[0103] The incremental data structuring unit can be configured to extract target incremental data from the incremental-prefetch database according to disease-specific incremental indicators, and perform structured processing on the target incremental data to obtain structured disease-specific indicator data.

[0104] In some example embodiments of the present disclosure, the retrieval statement generation module 620 can include a screening rule determination unit, which can be configured to determine a patient data screening rule based on the disease-specific configuration information selected by the user on the interactive configuration interface, and generate a corresponding disease-specific data retrieval statement according to the patient data screening rule.

[0105] In some example embodiments of the present disclosure, the screening rule determination unit can include a data inclusion / exclusion rule determination unit and a data screening rule determination unit. Wherein:

[0106] The data inclusion / exclusion rule determination unit can be configured to determine a disease-specific patient data inclusion rule based on disease-specific data inclusion configuration, and determine a disease-specific patient data exclusion rule based on disease-specific data exclusion configuration;

[0107] The data screening rule determination unit can be configured to determine a patient data screening rule according to the disease-specific patient data inclusion rule and the disease-specific patient data exclusion rule.

[0108] In some example embodiments of the present disclosure, the disease-specific database creation module 640 can include a disease-specific label adding unit, which can be configured to add a disease-specific label corresponding to the disease-specific database to the disease-specific patient data and generate a disease-specific data set.

[0109] The specific details of the modules / units in the above-mentioned apparatus for creating a disease database have been described in detail in the corresponding method embodiment part, and will not be described here again.

[0110] Figure 7 A structural schematic diagram of a computer system of an electronic device suitable for implementing embodiments of the present application is shown.

[0111] It should be noted that, Figure 7 The computer system 700 of the electronic device shown is only an example, and should not bring any limitation to the functions and use range of the embodiments of the present application.

[0112] As Figure 7 shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 702 or programs loaded from a storage portion 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for system operation are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0113] The following components are connected to the I / O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output portion 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage portion 708 including a hard disk, and the like; and a communication portion 709 including a network interface card such as a LAN card, a modem, and the like. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as necessary. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 710 as necessary, so that a computer program read therefrom is installed into the storage portion 708 as necessary.

[0114] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication portion 709, and / or installed from the removable medium 711. When the computer program is executed by the central processing unit (CPU) 701, various functions defined in the system of the present application are performed.

[0115] Note that the computer-readable medium shown in the disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium, for example, can be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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 above. In the disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. In the disclosure, the computer-readable signal medium can include a data signal that propagates in a baseband or as part of a carrier wave, in which the computer-readable program code is carried. Such a propagated data signal can take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium that is not a storage medium and that can be used to carry or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any suitable medium, including, but not limited to, wireless, wireline, optical fiber, RF, etc., or any suitable combination of the above.

[0116] The flow diagrams and block diagrams in the drawings are illustrations of possible architectures, functions, and operations of systems, methods, and computer program products in accordance with various embodiments of the present disclosure. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0117] As another aspect, the present application also provides a computer readable medium, which can be included in the electronic device described in the above embodiments, or can exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the method described in the above embodiments.

[0118] It should be noted that although several modules of the device for action execution are mentioned in the above detailed description, such a division is not mandatory. Indeed, according to embodiments of the present disclosure, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided into modules embodied by several modules.

[0119] Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the present application cover any and all variations of the present disclosure including modifications and adaptations thereof based on the general principles described herein and including variations individually known to those skilled in the art in this field of technology.

[0120] It is to be understood that the present disclosure is not limited to the precise construction described above and shown in the drawings, and that various modifications and changes can be effected therein by those skilled in the art without departing from the scope of the disclosure. The scope of the disclosure is to be limited only by the appended claims.

Claims

1. A method of creating a disease-specific database, characterized by, The method comprises the following steps: Based on a plurality of disease data models, obtain common indicators, and produce full-volume indicator data according to the common indicators; the common indicators refer to indicators that are not specific to a particular disease or discipline, have consistent and universal indicator processing logic in different disease data models, and are obtained by layering the disease data models and extracting the common indicators from each disease data model; An interactive configuration interface is provided on a user interface, and a corresponding disease data retrieval statement is generated based on the disease configuration information selected by the user on the interactive configuration interface; According to the disease data retrieval statement, corresponding disease patient data is obtained from the full-volume indicator data; According to the disease patient data, a disease data set is generated, and a corresponding disease database is created based on the disease data set.

2. The method of creating a disease-specific database according to claim 1, wherein The method comprises the following steps: Obtain full-volume patient data from a plurality of different data sources, and put the full-volume patient data into a full-volume preposition database; According to the common indicators, target full-volume data is extracted from the full-volume preposition database, and the target full-volume data is structured to obtain structured full-volume indicator data.

3. The method of claim 1, wherein the disease-specific database is created by, After creating the disease database, the method further comprises the following steps: Obtain disease incremental indicators corresponding to the disease database, and produce corresponding disease indicator data according to the disease incremental indicators.

4. The method of creating a disease-specific database according to claim 3, wherein The method comprises the following steps: Obtain the disease patient data from the disease database, and put the disease patient data into an incremental preposition database; According to the disease incremental indicators, target incremental data is extracted from the incremental preposition database, and the target incremental data is structured to obtain structured disease indicator data.

5. The method of claim 1, wherein the step of creating a disease-specific database comprises the step of: The method comprises the following steps: Based on the disease configuration information selected by the user on the interactive configuration interface, determine the patient data screening rules, and generate the corresponding disease data retrieval statement according to the patient data screening rules.

6. The method of creating a disease-specific database according to claim 5, wherein, The method comprises the following steps: Based on the disease data inclusion configuration, determine the corresponding disease patient data inclusion rules, based on the disease data exclusion configuration, determine the corresponding disease patient data exclusion rules, and determine the patient data screening rules according to the disease patient data inclusion rules and the disease patient data exclusion rules. The method comprises the following steps:

7. The method of creating a disease-specific database according to claim 1, wherein Add the disease label corresponding to the disease database to the disease patient data and generate the disease data set. The method comprises the following steps:

8. An apparatus for creating a disease-specific database, characterized by comprising: ​ The full-volume data production module is configured to obtain public indicators based on a plurality of disease-specific data models, and to produce full-volume indicator data according to the public indicators; the public indicators refer to indicators that are consistent in processing logic and are common in different disease-specific data models, and are obtained by layering the disease-specific data models and extracting the public indicators from each disease-specific data model; The search statement generation module is configured to provide a visual interactive configuration interface on a user interface, and to generate a corresponding disease-specific data search statement based on disease-specific configuration information selected by a user on the interactive configuration interface; The disease-specific data acquisition module is configured to acquire corresponding disease-specific patient data from the full-volume indicator data according to the disease-specific data search statement; The disease-specific database creation module is configured to generate a disease-specific data set according to the disease-specific patient data, and to create a corresponding disease-specific database according to the disease-specific data set.

9. An electronic device, comprising: comprise: a processor; and a memory for storing one or more programs, which, when executed by the processor, cause the processor to implement the method for creating a disease-specific database according to any one of claims 1 to 7. The programs, when executed by the processor, implement the method for creating a disease-specific database according to any one of claims 1 to 7.

10. A computer readable medium having stored thereon a computer program, characterized in that, ​

Images