Medical data processing method and device based on multiple hospital areas, electronic equipment and medium

Abstract

The invention provides a medical data processing method and device based on multiple hospital areas, electronic equipment, a computer readable storage medium and a computer program product, and relates to the field of computers, in particular to the technical field of knowledge graph, big data, artificial intelligence and medical data processing. According to the implementation scheme, in response to a first medical term received from a first mechanism, whether a first knowledge base corresponding to the first mechanism and a second knowledge base corresponding to a second mechanism comprise the first medical term or not is determined, and the second mechanism is a superior mechanism of the first mechanism; in response to determining that the second knowledge base comprises the first medical term, acquiring first medical data having an association relationship with the first medical term from the second knowledge base based on the knowledge inheritance type of the first mechanism; and carrying out association storage on the first medical term and the first medical data in a first knowledge base.

Description

Technical Field

[0001] The present disclosure relates to the field of computers, and in particular to the fields of knowledge graphs, big data, artificial intelligence, and medical data processing technology, and specifically to a medical data processing method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] With the gradual integration of the medical system and the Internet, the medical system has been vigorously developed by relying on the Internet. The Clinical Decision Support System (CDSS) of medical institutions is a computer-assisted information system that provides various forms of assistance to medical staff in clinical diagnosis and treatment activities and supports clinical decision-making by applying information technology and comprehensively analyzing medical knowledge and patient information. However, while the medical system is combined with the Internet, there are also some areas that need to be improved.

[0003] The methods described in this section are not necessarily methods that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any method described in this section is considered to be prior art simply because it is included in this section. Similarly, unless otherwise indicated, the issues mentioned in this section should not be considered to have been recognized in any prior art. Summary of the invention

[0004] The present disclosure provides a medical data processing method, apparatus, electronic device, computer-readable storage medium, and computer program product.

[0005] According to one aspect of the present disclosure, a medical data processing method is provided, comprising: in response to receiving a first medical term from a first institution, determining whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution; in response to determining that the second knowledge base includes the first medical term, based on a knowledge inheritance type of the first institution, acquiring first medical data having an association relationship with the first medical term from the second knowledge base; and storing the first medical term and the first medical data in association in the first knowledge base.

[0006] According to another aspect of the present disclosure, a medical data processing device is provided, including: a first determination unit, configured to, in response to receiving a first medical term from a first institution, determine whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution; a first acquisition unit, configured to, in response to determining that the second knowledge base includes the first medical term, acquire first medical data having an association relationship with the first medical term from the second knowledge base based on a knowledge inheritance type of the first institution; and a storage unit, configured to store the first medical term and the first medical data in association in the first knowledge base.

[0007] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in the present disclosure.

[0008] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided. The computer instructions are used to cause a computer to execute the method described in the present disclosure.

[0009] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, which implements the method described in the present disclosure when executed by a processor.

[0010] According to one or more embodiments of the present disclosure, the commonalities between superior and subordinate medical institutions can be replicated through certain logic, thereby reducing system redundant storage and improving performance; the medical institutions can implement customized knowledge maintenance, rapid sharing and collaborative application of medical knowledge, and ensure the quality homogeneity of diagnosis, treatment and operations among the medical institutions.

[0011] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings exemplarily illustrate the embodiments and constitute a part of the specification, and together with the text description of the specification, are used to explain the exemplary implementation of the embodiments. The embodiments shown are for illustrative purposes only and do not limit the scope of the claims. In all drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0013] Figure 1A schematic diagram showing an exemplary system in which the various methods described herein may be implemented according to an embodiment of the present disclosure;

[0014] Figure 2 A flowchart of a medical data processing method according to an embodiment of the present disclosure is shown;

[0015] Figure 3 A structural block diagram of a medical data processing device according to an embodiment of the present disclosure is shown; and

[0016] Figure 4 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0017] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0018] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0019] The terms used in the description of various examples in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. In addition, the term "and / or" used in this disclosure covers any one of the listed items and all possible combinations.

[0020] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0021] Figure 1 FIG. 1 is a schematic diagram of an exemplary system 100 in which various methods and apparatuses described herein may be implemented according to an embodiment of the present disclosure. Figure 1, the system 100 includes one or more client devices 101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

[0022] In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the method of medical data processing to be performed.

[0023] In some embodiments, server 120 may also provide other services or software applications, which may include non-virtualized environments and virtualized environments. In some embodiments, these services may be provided as web-based services or cloud services, such as provided to users of client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0024] exist Figure 1 In the configuration shown, the server 120 may include one or more components that implement the functions performed by the server 120. These components may include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 may in turn utilize one or more client applications to interact with the server 120 to utilize the services provided by these components. It should be understood that a variety of different system configurations are possible, which may differ from the system 100. Therefore, Figure 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

[0025] A user may use client devices 101, 102, 103, 104, 105, and / or 106 to upload medical data, etc. The client device may provide an interface that enables a user of the client device to interact with the client device. The client device may also output information to the user via the interface. Figure 1 Only six client devices are depicted, but one skilled in the art will appreciate that the present disclosure may support any number of client devices.

[0026] Client devices 101, 102, 103, 104, 105 and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, game systems, thin clients, various messaging devices, sensors or other sensing devices, etc. These computer devices may run various types and versions of software applications and operating systems, such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as GOOGLE Chrome OS); or include various mobile operating systems, such as MICROSOFT Windows Mobile OS, iOS, Windows Phone, Android. Portable handheld devices may include cellular phones, smart phones, tablet computers, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Game systems may include various handheld game devices, Internet-enabled game devices, etc. Client devices are capable of executing various different applications, such as various Internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and may use various communication protocols.

[0027] The network 110 may be any type of network known to those skilled in the art that may support data communications using any of a variety of available protocols, including but not limited to TCP / IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a local area network (LAN), an Ethernet-based network, a token ring, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a blockchain network, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0028] Server 120 may include one or more general purpose computers, dedicated server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running virtual operating systems, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain a server's virtual storage device). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0029] The computing units in the server 120 may run one or more operating systems including any of the above operating systems and any commercially available server operating systems. The server 120 may also run any of a variety of additional server applications and / or middle-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0030] In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0031] In some embodiments, the server 120 may be a server of a distributed system, or a server combined with a blockchain. The server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in a cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

[0032] The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as medical terms, medical knowledge. The database 130 may reside in various locations. For example, the database used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The database 130 may be of different types. In some embodiments, the database used by the server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve data to and from the database in response to a command.

[0033] In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the applications may be different types of databases, such as a key-value store, an object store, or a conventional store backed by a file system.

[0034] Figure 1The system 100 may be configured and operated in various ways to enable the application of various methods and apparatuses described in the present disclosure.

[0035] In recent years, the development of multiple campuses of public hospitals in my country has been rapid. Many medical institutions in nearly 100 regions across the country have started to build branch hospitals. For example, for large urban hospitals, most of them are located in the main urban area, and there are generally practical problems such as limited development space, overloaded services, and high bed utilization rates. The one-hospital-multiple-campus model can better solve the problem of space limitations, and can also alleviate overloaded services to a certain extent, and realize the sinking and expansion of high-quality medical resources.

[0036] The construction of multiple campuses requires the integration of resources within different campuses for horizontal unified management. When constructing a medical service system, it is generally a private deployment to support a single hospital, with several campuses deploying several systems. Each campus builds its own system, resulting in a waste of duplication of application costs and duplication of operation and maintenance costs. At the same time, the capabilities of the application systems of each campus vary, and the degree of standardization varies, which is not conducive to inter-hospital evaluation and information exchange.

[0037] The Clinical Decision Support System (CDSS) of medical institutions is a computer-assisted information system that uses information technology to comprehensively analyze medical knowledge and patient information, provide various forms of assistance to medical staff in clinical diagnosis and treatment activities, and support clinical decision-making. In order to meet the goal of sharing one set of CDSS in multiple districts of a hospital, the CDSS knowledge base management needs to be upgraded from a single hospital to multiple districts. Considering that multiple districts are managed uniformly but have differences, the knowledge base management module needs to support the construction of a knowledge system that has both commonalities and differences.

[0038] Therefore, according to an embodiment of the present disclosure, a medical data processing method is provided. Figure 2 A flowchart of a medical data processing method according to an embodiment of the present disclosure is shown. Figure 2 As shown, method 200 includes: in response to receiving a first medical term from a first institution, determining whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution (step 210); in response to determining that the second knowledge base includes the first medical term, based on the knowledge inheritance type of the first institution, obtaining first medical data having an association relationship with the first medical term from the second knowledge base (step 220); and storing the first medical term and the first medical data in association in the first knowledge base (step 230).

[0039] According to the embodiments of the present disclosure, the commonalities between superior and subordinate medical institutions can be replicated through certain logics, thereby reducing system redundant storage and improving performance; customized knowledge maintenance, rapid sharing and collaborative application of medical knowledge can be achieved between medical institutions, and the quality of diagnosis, treatment and operations among various medical institutions can be ensured to be homogeneous.

[0040] In the present disclosure, the knowledge base may include a data storage area or a database, which is not limited herein.

[0041] In some examples, medical terms may be derived from medical data. For example, medical data may be derived from medical records, etc. Medical records may include records of medical activities such as examination, diagnosis, treatment, and diagnosis results of one or more diseases of a patient. Medical data may be, for example, text data of a medical record. Alternatively, medical data may also include keywords and knowledge related to the diagnosis and treatment process or medical knowledge. Accordingly, in the case where medical data includes keywords related to the diagnosis and treatment process or medical knowledge, the medical term may be the keyword, or a word that has the same meaning as the keyword and meets the medical terminology standards.

[0042] In some examples, medical terms may be extracted from the medical data. Optionally, when extracting medical terms, the medical data may be extracted in parallel, that is, multiple terms in the medical data may be extracted at the same time, for example, medicines, diseases, symptoms, etc. in the medical data may be extracted at the same time. In some examples, the medical terms may include: department, diagnosis, medicine, examination, test, surgery, blood component, treatment, material, nursing, syndrome type, treatment method, therapy name, etc.

[0043] In some examples, the knowledge corresponding to the medical term may include detailed information related to the medical term, such as risk warnings and recommended rules that may occur during the diagnosis and treatment process, which is not limited here.

[0044] In some examples, medical terms may include drugs, diseases, symptoms, examinations, surgery names, CT images, etc. Among them, drugs can be extracted from drug use information, diseases can be extracted from disease information, symptoms can be extracted from disease symptoms, examinations can be extracted from disease examination information, surgery names can be extracted from disease surgery name information, and CT images can be extracted from disease examination information.

[0045] In some examples, there may be multiple sources of medical terms or medical data, such as a medical record homepage statistics system, a Hospital Quality Monitoring System (HQMS) system, an electronic medical record system, a Diagnosis Related Groups (DRG) platform, etc.

[0046] According to some embodiments, the medical terms in the corresponding knowledge base are stored in the form of a knowledge graph.

[0047] Generally, building a knowledge graph requires knowledge extraction from the accessed data. By connecting to a database or importing documents, structured relational data that can be understood and calculated by computers is extracted from data of different structures and types, and the data source is converted into knowledge graph data. In the knowledge base, medical terms (or entities) can be stored in association with each other. For example, a medical term can be the name of a data table, or the name of a data domain, or the noun of a data field.

[0048] In some examples, the knowledge graph can be structured and indexed to convert the complex knowledge graph into a structured data format that is easy to store, retrieve, and apply. By establishing a multidimensional index structure, the retrieval efficiency of the data is improved, so that the knowledge graph not only contains rich medical knowledge and relationships, but also has good structure and operability.

[0049] In some examples, management operations on the knowledge base can also be implemented based on the knowledge management platform, including operations such as querying, adding, deleting, modifying, and counting data in the knowledge base. Specifically, in response to a data update request from the backend of the knowledge management platform, the target entity can be determined from the knowledge base based on the entity identifier carried in the data update request. The entity data of the target entity is updated using the change data carried in the data update request.

[0050] In some examples, the acquired medical terms may be standardized to obtain a first medical term. For example, in response to receiving medical data, at least one first feature word is extracted from the medical data. The at least one first feature word is processed using a standard term library to obtain at least one second feature word. Based on the at least one second feature word, the first medical term is determined.

[0051] In some examples, at least one first feature word can be extracted from the medical data using a keyword extraction method in natural language processing.

[0052] In some embodiments, medical terms may be inconsistent between different medical institutions, such as stage 2 diabetes, type II diabetes, type 2 diabetes, and secondary diabetes. However, it is understandable that their substantial meanings are the same. Therefore, in some examples, when determining whether the corresponding medical term is included in the corresponding knowledge base, "include" here can mean "exactly the same" and "substantially the same".

[0053] According to some embodiments, method 200 may further include: in response to receiving a first medical term from a first institution, determining whether a third knowledge base corresponding to a third institution includes the first medical term, wherein the third institution is a subordinate institution of the first institution; in response to determining that the third knowledge base includes the first medical term, receiving first medical data corresponding to the first medical term from the first institution; and based on the knowledge inheritance type of the third institution, updating the medical data associated with the first medical term in the third knowledge base according to the first medical data.

[0054] In the above embodiment, by updating the medical data associated with the first medical term in the third knowledge base based on the knowledge inheritance type of the third institution according to the first medical data, the data integration between superior and subordinate medical institutions is ensured to ensure the quality homogeneity of diagnosis and treatment and operations in each hospital area.

[0055] In some examples, in the above-mentioned multi-campus construction scenario, the first medical institution may be a main hospital or a branch hospital. When the first medical institution is a branch hospital, its superior medical institution may be a main hospital; when the first medical institution is a main hospital, its subordinate medical institution may be a branch hospital.

[0056] According to some embodiments, the knowledge inheritance type includes at least one of the following items: full inheritance, partial inheritance, and full independence. Full inheritance means that the corresponding medical institution inherits all medical terms from its superior institution; partial inheritance means that the corresponding medical institution inherits some medical terms from its superior institution; and full independence means that the corresponding medical institution does not inherit any medical terms from its superior institution.

[0057] Full inheritance means that the corresponding medical institution inherits all medical terms in its superior institution. In some examples, when the knowledge inheritance type corresponding to the subordinate institution (i.e., child institution) is full inheritance, the subordinate institution inherits all medical terms of its superior institution (i.e., parent institution). And, when the corresponding medical terms include corresponding knowledge, the subordinate institution inherits all terms and their corresponding knowledge of its superior institution (i.e., parent institution). For example, after the parent institution uploads or adds new medical terms, the child institution can automatically pull the terms and knowledge of the parent institution.

[0058] In some examples, it is set that the terms and knowledge inherited from the parent organization cannot be modified or deleted; alternatively, it is set that the terms and knowledge inherited from the parent organization can be modified or deleted, and there is no limitation here.

[0059] Partial inheritance means that the corresponding medical institution inherits some medical terms from its parent institution. In some examples, the child institution can inherit the medical terms of the parent institution according to its actual needs.

[0060] According to some embodiments, when the knowledge inheritance type includes partial inheritance, the corresponding medical organization inherits the partial medical terms in its superior organization according to a dictionary table.

[0061] For example, after the parent organization uploads or adds new terms, the child organization inherits the medical terms in the form of a dictionary table. For example, if the dictionary table includes the same medical terms as the parent organization, the medical terms and their corresponding knowledge in the parent organization can be automatically pulled. Medical terms that do not exist in the dictionary table are private terms of the child organization and can be maintained by itself.

[0062] Full independence means that the corresponding medical institution does not inherit the terminology and knowledge of the parent institution at all. In some examples, full independence means that the corresponding medical institution does not inherit the terminology and knowledge of the parent institution at all, that is, the parent institution and the child institution are maintained completely independently.

[0063] Therefore, in some embodiments, when the knowledge inheritance type of the first institution is a full inheritance type, first medical data having an association relationship with the first medical term can be obtained from the second knowledge base; when the knowledge inheritance type of the first institution is a partial inheritance type, if the first medical term is included in the dictionary table corresponding to the first institution, the first medical data having an association relationship with the first medical term can be obtained from the second knowledge base, otherwise the first medical data having an association relationship with the first medical term is created by itself; when the knowledge inheritance type of the first institution is a full independent type, the first medical data having an association relationship with the first medical term is created by itself.

[0064] In some embodiments, when the knowledge inheritance type of the third institution is a full inheritance type, or the knowledge inheritance type of the third institution is a partial inheritance type and the first medical term is included in the dictionary table corresponding to the third institution, the medical data associated with the first medical term in the third knowledge base can be updated according to the first medical data; otherwise, the medical data associated with the first medical term in the third knowledge base is independent of the corresponding medical term and medical data in the first institution, and can be maintained by itself.

[0065] By setting the knowledge inheritance type, different modes can be set between medical institutions in various dimensions. For example, if a set of disease codes is shared between hospitals, all disease knowledge can be inherited. If there are differences in examinations, the examination knowledge can be set to be partially inherited or completely independent. Common knowledge can be maintained uniformly, and independent knowledge can be managed by personnel with corresponding permissions.

[0066] In some embodiments, multiple medical institutions can be supported to jointly maintain and manage medical terminology. In some examples, the corresponding medical institutions and their knowledge inheritance methods can be configured according to the authority of the medical institution or management personnel. For example, setting the existence authority of the superior medical institution can configure the knowledge inheritance method of its subordinate medical institutions, and the configuration will take effect on the medical institution and its subordinate medical institutions; the subordinate medical institutions can be set to have no knowledge inheritance method configuration authority.

[0067] According to some embodiments, the first medical term includes at least one of a first-level medical term and a second-level medical term, and the second-level medical term is a fine-grained classification of the first-level medical term. Wherein, determining whether the knowledge base corresponding to the corresponding institution includes the first medical term includes: in response to determining that the first medical term from the first institution is a second-level medical term, determining the first-level medical term corresponding to the second-level medical term of the first institution; and determining whether the knowledge base corresponding to the corresponding institution includes the first-level medical term and whether the fine-grained classification of the first-level medical term includes the first medical term.

[0068] In some embodiments, the first-level medical terms and the second-level medical terms are not fixed term attributes. When a medical term has a corresponding more fine-grained term classification, it can be a first-level medical term and its fine-grained term can be a second-level medical term; when the medical term also has a corresponding more coarse-grained term classification, the medical term becomes a second-level medical term relative to the coarse-grained term.

[0069] In some examples, a certain medical term may include multiple secondary medical terms. For example, for the medical term "diagnosis", it can be subclassified into: "diagnosis-specific population, diagnosis-specific age, diagnosis-positive features with diagnostic significance (symptoms / signs / tests / examinations)", etc.; for the medical term "examination", it can be subclassified into: "examination-contraindication symptoms, examination-contraindication diseases, examination-contraindication history, examination-conflicting items, examination-drug effects", etc.; for the medical term "blood transfusion", it can be subclassified into: "blood transfusion-physiological state, blood transfusion-contraindication signs, blood transfusion-contraindication diseases", etc. This expression is the relationship between medical terms.

[0070] Therefore, when the first medical term from the first institution is determined to be a secondary medical term, the medical term in the corresponding knowledge base is determined to be a medical term under the corresponding term branch to ensure the accuracy and completeness of the medical system constructed based on the method disclosed herein.

[0071] According to some embodiments, the first medical term includes an event-type term, and the event-type term includes at least one conditional information for forming an event corresponding to the event-type term. Determining whether the knowledge base corresponding to the corresponding institution includes the first medical term includes: determining whether the knowledge base corresponding to the corresponding institution includes the event-type term and the at least one conditional information corresponding to the event-type term.

[0072] In some examples, medical terms include event-type terms, that is, event-type terms are configured based on one or more conditions. For example, for the medical term "neonatal jaundice", the event corresponding to the term needs to include two conditions, condition 1: "age 0-12 hours" (that is, guaranteed to be a newborn), condition 2: "total bilirubin-serum greater than 65umol / L"; for the medical term "abnormal coagulation function", the event corresponding to the term needs to include two conditions, condition 1: "coagulation function PT greater than 15s", condition 2: "APTT greater than 48s".

[0073] According to some embodiments, the method 200 may further include: in response to determining that the first knowledge base includes the first medical term, generating prompt information, through which prompt information, instant feedback is provided to the user or system administrator.

[0074] According to the embodiments of the present disclosure, Figure 3 As shown, a medical data processing device 300 is also provided, including: a first determining unit 310, configured to determine, in response to receiving a first medical term from a first institution, whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution; a first acquiring unit 320, configured to acquire, in response to determining that the second knowledge base includes the first medical term, first medical data having an association relationship with the first medical term from the second knowledge base based on the knowledge inheritance type of the first institution; and a storage unit 330, configured to store the first medical term and the first medical data in the first knowledge base in an associated manner.

[0075] Here, the operations of the above-mentioned units 310-330 of the medical data processing device 300 are similar to the operations of the steps 210-230 described above, and will not be repeated here.

[0076] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0077] According to an embodiment of the present disclosure, an electronic device, a readable storage medium and a computer program product are also provided.

[0078] refer to Figure 4 , a block diagram of an electronic device 400 that can be used as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0079] like Figure 4 As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0080] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 can be any type of device that can input information to the electronic device 400. The input unit 406 can receive input digital or character information and generate key signal input related to user settings and / or function control of the electronic device, and can include but is not limited to a mouse, a keyboard, a touch screen, a track pad, a track ball, a joystick, a microphone, and / or a remote controller. The output unit 407 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 408 can include but is not limited to a disk, an optical disk. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, an 802.11 device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0081] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as method 200. For example, in some embodiments, the method 200 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the method 200 described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the method 200 in any other appropriate manner (e.g., by means of firmware).

[0082] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0083] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0084] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0085] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0086] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0087] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0088] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0089] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but only by the claims after authorization and their equivalent scope. Various elements in the embodiments or examples can be omitted or replaced by their equivalent elements. In addition, each step can be performed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples can be combined in various ways. It is important that with the evolution of technology, many elements described herein can be replaced by equivalent elements that appear after the present disclosure.

Claims

1. A medical data processing method, comprising: In response to receiving a first medical term from a first institution, determining whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution; In response to determining that the second knowledge base includes the first medical term, based on the knowledge inheritance type of the first organization, obtaining first medical data having an association relationship with the first medical term from the second knowledge base; and The first medical term and the first medical data are associated and stored in the first knowledge base.

2. The method of claim 1, further comprising: In response to receiving a first medical term from a first institution, determining whether a third knowledge base corresponding to a third institution includes the first medical term, wherein the third institution is a subordinate institution of the first institution; In response to determining that the first medical term is included in the third knowledge base, receiving first medical data corresponding to the first medical term from the first institution; and Based on the knowledge inheritance type of the third organization, the medical data associated with the first medical term in the third knowledge base is updated according to the first medical data.

3. The method according to claim 1 or 2, further comprising: In response to determining that the first knowledge base includes the first medical term, prompt information is generated.

4. The method according to any one of claims 1 to 3, wherein: The first medical term includes at least one of a primary medical term and a secondary medical term, wherein the secondary medical term is a fine-grained classification of the primary medical term, wherein determining whether the knowledge base corresponding to the corresponding institution includes the first medical term includes: In response to determining that the first medical term from the first institution is a second-level medical term, determining a first-level medical term corresponding to the second-level medical term of the first institution; and It is determined whether the knowledge base corresponding to the corresponding institution includes the first-level medical term and whether the fine-grained classification of the first-level medical term includes the first medical term.

5. The method according to any one of claims 1 to 3, wherein: The first medical term includes an event-type term, and the event-type term includes at least one conditional information for forming an event corresponding to the event-type term, wherein determining whether the knowledge base corresponding to the corresponding institution includes the first medical term includes: in response to determining that the first medical term from the first institution is an event-type term, determining whether the knowledge base corresponding to the corresponding institution includes the event-type term and the at least one conditional information corresponding to the event-type term.

6. The method according to any one of claims 1 to 5, wherein: The knowledge inheritance type includes at least one of the following items: full inheritance, partial inheritance and full independence, wherein: The full inheritance means that the corresponding medical institution inherits all medical terms in its superior institution; The partial inheritance means that the corresponding medical institution inherits some medical terms from its superior institution; The "all independent" means that the corresponding medical institution does not inherit the medical terminology from its superior institution.

7. The method of claim 6, wherein: When the knowledge inheritance type includes partial inheritance, the corresponding medical institution inherits the part of medical terms in its superior institution according to the dictionary table.

8. The method according to any one of claims 1 to 7, wherein: The medical terms in the corresponding knowledge base are stored in the form of knowledge graphs.

9. A medical data processing device, comprising: a first determining unit configured to, in response to receiving a first medical term from a first institution, determine whether a first knowledge base corresponding to the first institution and a second knowledge base corresponding to a second institution include the first medical term, wherein the second institution is a superior institution of the first institution; a first acquisition unit configured to, in response to determining that the second knowledge base includes the first medical term, acquire first medical data having an association relationship with the first medical term from the second knowledge base based on the knowledge inheritance type of the first institution; and The storage unit is configured to store the first medical term and the first medical data in association with each other in the first knowledge base.

10. The apparatus of claim 9, further comprising: a second determining unit configured to, in response to receiving the first medical term from the first institution, determine whether a third knowledge base corresponding to a third institution includes the first medical term, wherein the third institution is a subordinate institution of the first institution; a second acquisition unit configured to receive first medical data corresponding to the first medical term from the first institution in response to determining that the first medical term is included in the third knowledge base; and An updating unit is configured to update the medical data associated with the first medical term in the third knowledge base according to the first medical data based on the knowledge inheritance type of the third institution.

11. The device according to claim 9 or 10, further comprising: The prompt unit is configured to generate prompt information in response to determining that the first knowledge base includes the first medical term.

12. The device according to any one of claims 9 to 11, wherein: The first medical term includes at least one of a primary medical term and a secondary medical term, wherein the secondary medical term is a fine-grained classification of the primary medical term, wherein the corresponding determination unit includes: a unit for determining, in response to determining that the first medical term from the first institution is a second-level medical term, a first-level medical term corresponding to the second-level medical term of the first institution; and A unit for determining whether the knowledge base corresponding to the corresponding institution includes the first-level medical term and whether the fine-grained classification of the first-level medical term includes the first medical term.

13. The device according to any one of claims 9 to 11, wherein: The first medical term includes an event-type term, and the event-type term includes at least one conditional information for forming an event corresponding to the event-type term, wherein the corresponding determination unit includes: a unit for determining, in response to determining that the first medical term from the first institution is an event-type term, whether a knowledge base corresponding to the corresponding institution includes the event-type term and the at least one conditional information corresponding to the event-type term.

14. The device according to any one of claims 9 to 13, wherein: The knowledge inheritance type includes at least one of the following items: full inheritance, partial inheritance and full independence, wherein: The full inheritance means that the corresponding medical institution inherits all medical terms in its superior institution; The partial inheritance means that the corresponding medical institution inherits some medical terms from its superior institution; The "all independent" means that the corresponding medical institution does not inherit the medical terminology from its superior institution.

15. The device of claim 14, wherein: When the knowledge inheritance type includes partial inheritance, the corresponding medical institution inherits the part of medical terms in its superior institution according to the dictionary table.

16. The device according to any one of claims 9 to 15, wherein: The medical terms in the corresponding knowledge base are stored in the form of knowledge graphs.

17. An electronic device comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

18. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-8.

19. A computer program product comprising a computer program, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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