CN113990518B - Information generation method, device, electronic equipment and storage medium - Google Patents

Abstract

The disclosure provides an information generation method, an information generation device, electronic equipment and a storage medium, relates to the technical field of computers, and particularly relates to the technical field of artificial intelligence such as knowledge graph and AI medical treatment. The specific implementation scheme is as follows: generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information; in the knowledge information, determining knowledge to be reminded when diagnostic information is generated according to the diagnostic information generation instruction; and generating reminding information according to the knowledge required to be reminded. Embodiments of the present disclosure are capable of providing effective assistance and support for medical activity.

Description

Information generation method, device, electronic equipment and storage medium

Technical Field

The disclosure relates to the field of computer technology, in particular to the technical field of artificial intelligence such as knowledge graph and AI medical treatment.

Background

With the development of computer technology, the quality and efficiency of various aspects of life of people are improved, for example, clothing and food residence can obtain a better and efficient life experience through the computer technology.

In addition to clothing and eating, medical treatment is also an extremely important aspect of people's life. In general, the medical process has strong dependence on subjective ability of medical staff, so there are many possible hidden hazards in the process of medical behaviors, for example, human judgment may be wrong to cause serious life health problems, and medical knowledge data volume is extremely large so that omission and the like are easy to occur under special conditions. With the development of computer technology, better application of computer technology to the medical field can be considered, and the quality and efficiency of medical procedures can be improved.

Disclosure of Invention

The disclosure provides an information generation method, an information generation device, electronic equipment and a storage medium.

According to an aspect of the present disclosure, there is provided an information generating method including:

generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information;

in the knowledge information, determining knowledge to be reminded when diagnostic information is generated according to the diagnostic information generation instruction;

and generating reminding information according to the knowledge required to be reminded.

According to another aspect of the present disclosure, there is provided an information generating apparatus including:

the knowledge information acquisition module is used for generating an instruction according to the received diagnosis information to acquire corresponding knowledge information;

the knowledge determination module is used for determining knowledge required to be reminded when the diagnosis information is generated according to the diagnosis information generation instruction in the knowledge information;

and the reminding information generation module is used for generating reminding information according to knowledge required to be reminded.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of any of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program/instruction which, when executed by a processor, implements the method in any of the embodiments of the present disclosure.

According to the technology disclosed by the invention, whether matters needing reminding or attention exist or not can be judged according to the diagnosis information generation instruction and the medical knowledge information, so that good support and auxiliary effects can be provided for medical diagnosis activities, and the reliability of medical diagnosis behaviors is improved.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow diagram of a method of generating information according to an embodiment of the present disclosure;

FIG. 2 is a flow chart of an information generation method according to another embodiment of the present disclosure;

fig. 3 is a schematic diagram of a CDSS system architecture according to an example of the present disclosure;

FIG. 4A is a schematic diagram of a knowledge management flow in accordance with an example of the present disclosure;

FIG. 4B is a schematic diagram of knowledge disambiguation according to an example of the present disclosure;

FIG. 5 is a schematic diagram of knowledge information content in accordance with an example of the present disclosure;

FIG. 6 is a functional module configuration schematic according to an example of the present disclosure;

FIG. 7 is a schematic diagram of a personnel management architecture according to an example of the present disclosure;

FIG. 8 is a log statistics schematic diagram according to an example of the present disclosure;

FIG. 9 is a schematic diagram of an information generating apparatus according to an embodiment of the present disclosure;

fig. 10 is a schematic diagram of an information generating apparatus according to another embodiment of the present disclosure;

FIG. 11 is a schematic diagram of an information generating apparatus according to yet another embodiment of the present disclosure;

fig. 12 is a schematic diagram of an information generating apparatus according to still another embodiment of the present disclosure;

fig. 13 is a schematic diagram of an information generating apparatus according to still another embodiment of the present disclosure;

FIG. 14 is a schematic illustration of a presentation interface according to an example of the present disclosure;

fig. 15 is a block diagram of an electronic device used to implement a method of information generation method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The embodiment of the disclosure first provides an information generating method, as shown in fig. 1, including:

step S11: generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information;

step S12: in the knowledge information, determining knowledge to be reminded when diagnostic information is generated according to the diagnostic information generation instruction;

step S13: and generating reminding information according to the knowledge required to be reminded.

In this embodiment, the diagnostic information generation instruction may be a diagnostic information generation instruction which is generated in response to various medical activities such as diagnosis, examination, bundling, drug delivery, surgery, injection, and report on the occasion of performing various medical activities such as medical treatment and medical treatment-related activities, or may be a diagnostic information generation instruction which is generated in response to any objective billing action performed by the medical staff.

The diagnostic information generation instructions may be instructions to generate diagnostic information for individual patients.

The corresponding knowledge information can be any medical behavior related to the diagnosis information generation instruction or knowledge information related to medical supplies and medicines. For example, the diagnostic information generation instruction is used to generate an inspection sheet, and the inspection sheet needs to use the instrument a and the medicine B, and the relevant knowledge information may be knowledge information of the instrument a and the medicine B.

The knowledge information may also include objective knowledge information that needs to be given special attention in medical activities, or knowledge information related to set security rules.

For example, the diagnostic information generation instructions are used to generate an examination order that requires the use of the instrument a and the drug B, and the relevant knowledge information may be knowledge information of the instrument a and the drug B, which may include special safety conditions for the use of the instrument a and the drug B, requirements for the patient, or the type of patient to be adapted, and so on.

The knowledge information may also include subjective information that may be changed or personnel information that may be changed obtained during a medical activity, such as patient registration information, information about the patient that a medical staff person manually records during the medical activity.

The knowledge information may include knowledge that needs to be reminded when generating the diagnostic information, such as various requirements, matters needing attention, special processing mode specifications, and content easy to be missed in the diagnostic information generation instruction and the knowledge information.

For example, there may be several alternative examination methods for the same medical index or disease, but there may be differences in patients for whom different examination methods may be applicable, such as some examination methods for patients without a certain major disease, some examination methods for adult patients, some examination methods for elderly patients, etc.

In the knowledge information, according to the diagnosis information generation instruction, determining knowledge required to be reminded when the diagnosis information is generated may further include determining whether the diagnosis information to be generated by the current medical staff is likely to have an error against the knowledge information according to the diagnosis information generation instruction and the knowledge information. For example, an underage patient prescribes an examination order in an examination manner suitable for an adult.

The reminding information can be generated in the form of popup boxes and the like according to the knowledge required to be reminded, and the knowledge required to be reminded is displayed in the form of characters, images and the like, so that medical staff sending information generation instructions can intuitively see the reminding information.

The embodiments of the present disclosure may be applied to a clinical decision-making system (Clinical Decision Support System, CDSS) for medical use, generally referred to as a computer system capable of supporting clinical decisions, which fully uses available and suitable computer technology, and aims at semi-structured or unstructured medical problems, and improves and enhances decision-making efficiency by means of man-machine interaction. The CDSS builds and maintains a medical knowledge graph through learning authoritative teaching materials, guidelines, high-quality medical records of three hospitals and the like, builds a multi-model decision system based on AI (Artificial Intelligence ) technology such as medical knowledge graph, natural language processing and the like, strictly follows the rule of medical evidence following, and is suitable for all-in-hospital scenes such as emergency diagnosis, ward, inspection and inspection departments, pharmacy, nursing and the like. The CDSS system provides clinical decision support services such as auxiliary diagnosis, treatment scheme recommendation, similar medical record recommendation, medical advice quality control, medical record content quality control, medical knowledge query and the like for medical behaviors.

The embodiment of the disclosure can be particularly applied to a clinical auxiliary decision-making integrated platform of a CDSS system, namely a unified knowledge background management platform of a plurality of CDSS product lines. The CDSS front-end system is provided with a plurality of product lines such as a standard edition, a basic edition and reasonable medication, each product line needs a background knowledge management platform after falling to the ground, wherein the product lines have independent functions and general functions, and each product line can use the same set of medical knowledge, so that the CDSS integrated platform is designed and realized, the universality of the knowledge is improved, the reasonable division of the platform is improved, and the delivery standardization is improved.

In this embodiment, whether a matter requiring reminding or attention exists or not can be determined according to the diagnosis information generation instruction and the knowledge information of the medical treatment, so that good support and auxiliary effects can be provided for medical diagnosis activities, and the reliability of medical diagnosis behaviors can be improved.

In one embodiment, in the knowledge information, according to the diagnostic information generation instruction, determining knowledge that needs to be reminded when generating the diagnostic information includes:

and when the diagnosis information corresponding to the diagnosis information generation instruction conflicts with the first target knowledge information in the knowledge information, the first target knowledge information is used as knowledge to be reminded.

In this embodiment, the diagnostic information corresponding to the diagnostic information generating instruction may conflict with the first target knowledge information in the knowledge information, or may not meet the requirement of the first target knowledge information or violate the first target knowledge information.

The first target knowledge information may be a knowledge information, such as, for example, D-exam, suitable for class E patients.

The first target knowledge information may also be a combination of knowledge information, such as that the D-exam is applicable to class E patients, and the current patient is not a class E patient.

In this embodiment, when the first target knowledge information that is contrary to the diagnostic information exists in the knowledge information, information to be reminded is generated according to the first target knowledge information, that is, by means of display or the like, medical staff sending the diagnostic information generation instruction can watch or learn the first target knowledge information, so that the number of times of generating the diagnostic information in error is reduced as much as possible, repeated billing or performing wrong medical actions due to the fact that the diagnostic information is generated in error is avoided, and accuracy and efficiency of the medical actions are improved.

In one embodiment, in the knowledge information, according to the diagnostic information generation instruction, determining knowledge that needs to be reminded when generating the diagnostic information includes:

and when the diagnostic information to be generated by the diagnostic information generation instruction does not contain any notice required by the second target knowledge information in the knowledge information, the second target knowledge information is taken as knowledge required to be reminded.

The precautions required for the second target knowledge information in the knowledge information may be special precautions and preparation of the patient required for examination, or missing items of common medicines of the patient, and the like.

Specifically, for example, the requirement of preparing a medicine to be orally taken in advance, preparing a hollow medicine, stopping a special medicine, and the like may be satisfied in some examination items.

In this embodiment, the second target knowledge information that may be missed can be used as knowledge that needs to be reminded, and the reminder information is generated according to the second target knowledge information, so that important matters can be avoided being missed, and further, the low-efficiency conditions such as adding and changing the bill during the bill opening can be avoided, and the omission in the diagnosis information can also be avoided.

In one embodiment, the knowledge information includes at least one of:

medical first knowledge information of a target hospital for a patient visit;

patient information extracted from patient history diagnostic information;

patient information autonomously provided by the patient;

second knowledge information obtained from the knowledge inheritance hospital of the target hospital; the knowledge inheritance hospital is a hospital that can share the second knowledge information to the target hospital.

The medical first knowledge information of the target hospital for patient treatment can be knowledge information used in the target scope, can be derived from common medical knowledge or medical knowledge in a knowledge system built in the target hospital.

The patient information extracted from the patient history diagnosis information can be the patient history examination result, the specific physical conditions of the patient such as the current fracture, pregnancy, postoperative stage and the like, the special reaction of the patient after taking the specific medicine, the current disease of the patient, the chronic disease of the patient, the benign lesions in the patient body without short-term review, the benign lesions in the patient body with short-term review, the benign lesion degree of the patient, the malignant lesions possibly existing in the patient and the like.

In this embodiment, patient information autonomously provided by a patient may be information filled in by the patient when the patient registers patient information in a target hospital, or may be information provided by other people to assist patient registration and recording.

In this embodiment, the knowledge inherited hospital may be a hospital of the same system as the target hospital, for example, a hospital attached to the same F medical research institution, a hospital attached to the same G medical department higher education institution, or a hospital of a different address of the same hospital, or the like.

The knowledge inheritance hospital may be a hospital belonging to the same general medical category as the target hospital, such as a hospital belonging to the same specialty as the target hospital, a hospital belonging to the same class of traditional Chinese medicine as the target hospital, or the like.

The knowledge inherited hospital may be a hospital that has a set job transfer and job delivery relationship with a target. For example, the H-hospital is a third class first hospital, and is a third class first hospital, the I-community hospital is closest to the third class first hospital, so that medical work required to be transferred by the general default I-community hospital can be transferred to the H-hospital, the H-hospital can be a knowledge inheritance hospital of the I-community hospital, and the I-hospital can also be a knowledge inheritance hospital of the H-hospital.

The knowledge inheritance hospital may also be a specially preset hospital. For example, if a certain cooperative relationship exists between the H hospital and the J hospital, the H hospital and the J hospital can be mutually set as knowledge inheritance hospitals.

The knowledge inherited hospital may also be a superior hospital of the target hospital or a hospital at the same level as the target hospital.

In the embodiment, knowledge information can be obtained through various ways, so that the content of the knowledge information is greatly enriched, a more perfect knowledge graph is established, and the convenience, efficiency and accuracy of medical behaviors are improved.

In an embodiment, where the knowledge information includes medical first knowledge information of a target hospital for a patient visit, as shown in fig. 2, the method further includes:

step S21: acquiring autonomous medical knowledge information of a target hospital, wherein the autonomous medical knowledge information comprises autonomous terms used in the target hospital;

step S22: associating the autonomous terms with the general terms in the general medical knowledge information to obtain an association result;

step S23: and taking the association result, the autonomous medical knowledge information and the general medical knowledge information as first knowledge information.

The autonomous medical knowledge information of the target hospital may be medical knowledge information used inside the target hospital, such as medical research results of personnel inside the target hospital, usual habitual knowledge information inside the target hospital, and the like.

The general medical knowledge information may be standard means, standard expressed medical knowledge information known in the medical field, such as standard terms, standard definitions, standard operation specifications, standard medical specifications or specifications, and the like.

Associating the autonomous term with a generic term in the generic medical knowledge information may be associating the autonomous term with a standard term expressing the same meaning. For example, a standard name of a disease is associated with a generic abbreviation within the target hospital. For another example, medicines having the same number and different names are associated.

The association result, the autonomous medical knowledge information and the general medical knowledge information are used as the first knowledge information, and the autonomous medical knowledge information and the general medical knowledge information can be combined according to the association result, and the combined knowledge information is used as the first knowledge information.

In this embodiment, the autonomous medical knowledge information and the general medical knowledge information of the target hospital are associated to obtain the first knowledge information fused with the autonomous medical knowledge and the general medical knowledge of the target hospital, so that not only are the internal habits and achievements of the target hospital reserved, but also the general medical knowledge is utilized, the content of the knowledge is enriched, and further valuable reminding information can be provided for medical behaviors.

In one embodiment, the knowledge information includes knowledge information generated for original knowledge fields recorded from original files in the repository and/or knowledge field updates recorded from patch files of the original files.

In this embodiment, the original knowledge resource may be knowledge information that is initially acquired, and with development and update of knowledge, a patch file of the original file may be generated for a part of the updated knowledge, and the updated knowledge content is iterated by using the patch file part.

In the embodiment, part of knowledge content is updated in an iterative mode, instead of replacing all knowledge when new knowledge is generated, so that replacement time is saved, and replacement efficiency is improved.

In one embodiment, the diagnostic information generation instructions include instructions received by controlling a presentation interface, the generation process of the presentation interface including the steps of:

generating a front-end display assembly according to the customization information of the target hospital;

and generating a display interface according to the front-end display component.

In this embodiment, the customization information of the target hospital may be module information of the target hospital, for example, the generated modules are different for different hospitals. Custom information for the target hospital may be used to determine which modules specific to the target hospital need to be provided.

For example, in the case where the target hospital level is relatively low, only primary medical services are provided, the modules of the basic functions or primary function modules may be customized by customizing the information. In the case where the target hospital level is relatively high and high-level medical services are provided, the advanced function module or the standard function module can be provided by customizing the information.

In this embodiment, the same functional components of the same module may be reused, so that not only the utilization rate of the components may be improved, but also the development operation of the client of the target hospital may be reduced.

In one embodiment, the presentation interface includes a presentation item for receiving diagnostic information generation instructions; the method further comprises the steps of:

determining login rights according to the information of a login person logging in the display interface, wherein the login rights comprise default rights corresponding to the identity of the login person and rights authorized by an authorizer of the login person;

and determining the display item according to the login authority.

In this embodiment, the logger of the display interface may be a medical staff member. The login authority of the medical staff can be related to the positions and departments of the medical staff.

The login authority can be determined through verification information such as an account number, a password and the like used by a login person during login. The identity of the logger can be divided by level, and also can be divided by information such as specific departments.

For example, after a staff in a pharmacy logs in the display interface, the staff can check the information of all medicines, but the information of the functional modules for issuing medicines does not exist.

A presentation interface may include information in multiple dimensions as shown in fig. 14. In this embodiment, the authorizer of the registrant may be the upper level registrant of the registrant. The same administration can be done through the level for different loggers. The higher the level of registrants, the more information can be presented on the presentation interface. The login rights of the login persons of the same level may be the same or may be different due to the own properties of the login persons such as departments. The display interface of the upper level logger can display all information in the display interface of the lower level logger, and can authorize the information which does not exist in the display interface of the lower level logger to the lower level logger, so that the lower level logger can view other authorized information on the display interface.

In this embodiment, the corresponding display item can be determined according to the login authority of the login person, so that different information is displayed for different login persons, individuation of the display interface is realized, disorder of the display interface of the medical staff due to the fact that too much irrelevant content exists in the display information is avoided, and improvement of working efficiency and working convenience of the medical staff is facilitated.

In one embodiment, generating a front-end presentation component from customization information of a target hospital, comprises:

according to the customization information of the target hospital, determining the sub-components required by each section respectively;

determining a total set of sub-components required by a target hospital according to the sub-components required by each section;

and generating a front-end display component according to the sub-component total set and the basic configuration corresponding to the target hospital.

According to the embodiment, the front-end display component of the target hospital can be generated according to the specific customization information of the target hospital, so that the system configuration can be flexibly increased, and if a new module is added to a certain product line, only the functional module is required to be added under the corresponding configuration file. The unified management and the on-demand distribution of the CDSS system can be realized, and the delivery standardization of other hospital clients such as target hospitals is improved.

In one example of the disclosure, the CDSS integrated platform mainly has knowledge management, system management, personnel management, log inquiry, data statistics, medical records quality control, reasonable medication, license uploading and other large modules, wherein the most closely related with the CDSS system is the knowledge management module, the module manages the knowledge of 26 dimensions of medicines, operations, treatments, physical signs, custom crowd and the like, a target hospital acquires a corresponding medical knowledge to local Mongo database by uploading a term dictionary table on the platform, and a rule validation engine of the CDSS system can read the knowledge data to perform medical order quality control, medication quality control, diagnosis quality control function operation and the like. The term Knowledge is obtained by mapping the total Knowledge stored in advance into a local Mongo library through a disambiguation algorithm of KG (knowledgegraph).

In this example, the CDSS system architecture is shown in fig. 3. Specifically, the CDSS front-end system 31, the database part and the CDSS integrated platform 32 are included. The CDSS front-end system comprises standard edition, basic edition, reasonable medicine application and other edition blocks. The standard edition comprises functional units such as intelligent inquiry, diagnosis recommendation, treatment recommendation, document quality control, doctor's advice quality control, case knowledge retrieval and the like. The basic edition comprises functional units such as intelligent inquiry, auxiliary diagnosis, treatment recommendation, document quality control, diagnosis quality control, case knowledge retrieval and the like. Reasonable medication can include functional units such as medication quality control. The CDSS front-end system 31 is logged in and used by medical staff to generate diagnostic information and the like, and provides the functions of model calculation and rule engines. The CDSS integrated platform 32 is used for the management personnel of the target hospital to perform operations such as adding, deleting, and modifying data. The system specifically comprises functional units such as data statistics (BI, business Intelligence, business intelligence), knowledge management, system management, personnel management, medical records quality control, log inquiry, license uploading, reasonable medication and the like. Wherein the CDSS integration platform 32 can manage data stored in the database section through the CDSS integration platform 32. The data statistics function unit of the CDSS integrated platform 32 may obtain log files from the CDSS front-end system 31 for statistics, and the obtained statistics data may be stored in an ES (Elastic Search) database 33 of the database part. The database section also includes a Mongo database 34 for storing term knowledge, a full-quantity database 35 for storing full-quantity knowledge, and the like.

The target hospital 36 can fuse information such as autonomous knowledge used within the target hospital with the full amount of knowledge containing standard medical knowledge by uploading the term file to the CDSS integration platform 32.

The CDSS front-end system 31 provides clinical assistance to medical staff in the target hospital based on information stored in the database portion during the operation of the medical staff in the target hospital.

In the example of the disclosure, knowledge management is a core function of a CDSS integrated platform, a hospital can import the terms belonging to the hospital by uploading an in-hospital dictionary table, adding new terms and the like, the platform compares the full-quantity knowledge generated based on the medical knowledge graph in the full-quantity knowledge base with the uploaded terms through a disambiguation algorithm, and according to the comparison result, if the knowledge is successful, the knowledge is directly pulled into a Mongo database, if the knowledge is to be confirmed or fails, the manual intervention is needed for comparison, and the knowledge mapping is ensured to be correct.

In another specific example, the knowledge management flow is shown in FIG. 4A. The hospital internal glossary 41 is generated by the dictionary table in the hospital, the new internal knowledge, the data view and other files, and the hospital glossary 41 and the standard glossary are subjected to disambiguation processing by a disambiguation algorithm 42. In this example, the disambiguation may be an entity disambiguation, i.e. it may itself tend to have ambiguity for the named entity, resulting in the possible ambiguity of the terms uploaded by the target hospital, thus requiring disambiguation to correspond to the unique KG-standard medical knowledge. The target hospital glossary can be used as an input entity, and candidate data are pulled in the ES database according to the input entity for comparison.

In one particular implementation, for a drug, the pull policy may be that the drug name and manufacturer agree with the compared items in the internal glossary 41, i.e., are listed as candidate results. For each candidate result, in the internal glossary 41 and the standard glossary, feature extraction is performed according to the characteristics of the dosage form, the drug name, the national drug standard type, the specification, the manufacturer and the like of the drug. According to terms extracted from the standard glossary, which may be identical to the internal glossary 41, the relevant features are scored by traversing the rules from top to bottom, the rules being less tolerant.

Scoring rules can be divided into three by groups. The first may be a pre-filtration rule, such as direct filtration to filter drugs in a standard glossary in the event of inconsistent drug dosage forms.

The second may be a three attribute comparison rule. For pharmaceutical and non-pharmaceutical products, three gradients can be divided, including: the three attributes (medicine name, specification and manufacturer) are consistent, and the national medicine standard words are consistent. The three attributes (medicine name, specification, manufacturer) are all consistent. The Chinese medicine standard words are consistent.

The third can be to introduce new criteria for the two attribute comparison rule. For a drug, the manufacturer ignores the specification attribute when only one drug is used. In the case where both attributes (drug name, manufacturer) are identical and the national drug standard words are identical, or both attributes (drug name, manufacturer) are identical, the compared terms in the hospital glossary 41 and the terms in the standard glossary are considered to be identical.

The input entities of the internal glossary 41 are compared with candidate entities one by one to score, and the most scored terms are ranked and taken as the comparison glossary 44 in the comparison result.

For the internal glossary 41, the comparison result shows that whether the terms are consistent or not can not be determined, a catalog 431 to be confirmed can be generated, confirmation is carried out according to the subsequent confirmation information, and the comparison glossary 44 is supplemented according to the confirmation condition.

For the terms in the internal glossary 41, the comparison result shows that the terms cannot be matched in the standard glossary, the catalog 432 to be supplemented can be generated, the confirmation is carried out according to the subsequent supplementary information, and the comparison glossary 44 is supplemented according to the confirmation condition.

In a specific example, the data format in which the medical term knowledge of the CDSS integrated platform is stored in the Mongo database contains four fields, respectively: a term field for recording term information; a base field for recording the base knowledge after comparison; a patch field for recording an update of knowledge; and a data field for recording the current latest knowledge. When the term is disambiguated, standard medical knowledge in the full knowledge base is pulled and stored in the base field, in which case the data field is identical to the base field.

After the correspondence between the internal glossary 41 and the standard glossary is completely determined, the local glossary of the initial version is generated through the knowledge generation operation 45 and the full-quantity glossary of the initial version, and after the full-quantity glossary of the initial version is generated, the local glossary of the modified version can be obtained according to the full-quantity glossary of the modified version through manual operation and the like. In the event that updated knowledge occurs, an updated full or local knowledge table may be generated based only on the updated portions. In one specific example of the present disclosure, the disambiguation algorithm 42 may also be modified by a full or local knowledge table of the various versions.

In another example of the present disclosure, as shown in fig. 4B, the medical knowledge information disambiguation process includes:

step S46: and (5) inputting. Autonomous knowledge information of the target hospital is input.

Step S47: candidate pull. And pulling standard knowledge information which is possibly the same as each piece of independent knowledge information according to the independent knowledge information and the standard knowledge information of the target hospital.

Step S48: and (5) extracting characteristics. Feature extraction can be performed on the autonomous knowledge information and the pulled standard knowledge information. Features can be added, combined, modified and deleted through a feature manager, and the features can specifically comprise medicine polarity, article specification, name, manufacturer, national medicine standard word number and the like.

Step S49: and (5) sequencing. And sequencing the candidate standard knowledge information according to the similarity of the pulled candidate standard knowledge information and the autonomous knowledge information aiming at each piece of autonomous knowledge information.

Step S410: and outputting. And outputting the closest standard knowledge information aiming at each piece of independent knowledge information.

In a specific example, a structured (Structure) or Semi-structured (Semi-structured) or structured and Semi-structured combined Knowledge database (KB) may be used to store all Knowledge information of the target hospital, and the Knowledge retrieval is performed by means of ES.

In a specific example, the update of the knowledge field can be recorded with a JSON Patch (JavaScript Object Notation Patch, JS object profile Patch) component. JSON Patch is a format that describes changes to JSON documents that can be used to avoid sending the entire document when only a portion changes. When JSON Patch is used in conjunction with HTTP (Hyper Text Transfer Protocol ) Patch methods, partial updates to HTTP APIs (Application Programming Interface, application program interfaces) may be allowed in a standard compliant manner. Common operations include add (add), remove (remove), replace (replace). Thus, specifically, the Patch file generated by the JSON Patch component in combination with the HTTP Patch component may be employed in examples of the present disclosure.

Every time knowledge is updated, the CDSS front end only needs to send patch files to inform the change data instead of sending the full knowledge data. After the CDSS integrated platform receives the changed data, the latest data field is obtained through calculation through the base field and the patch field, the changed data in the patch file is also reserved in the patch field, a follow-up operation recording module reads the patch field to present the difference between before and after the knowledge update, and as shown in fig. 5, information such as operation types, specific indexes, operators, operation contents and the like is recorded. The disclosed example is capable of fully recording all changes of medical knowledge in the database portion over the life cycle, all data related to the index, including various operation records composed of operation type (modification, addition or deletion, etc.), operation time, operation content, etc.

In a specific implementation manner, considering that more than one community health service center of the basic medical area can be used, the term knowledge of each community health service center can be different, and the same term knowledge can be adopted in the whole area, in order to solve the situation, the CDSS integrated platform of the disclosed example realizes knowledge inheritance of multiple institutions in the area. The mechanism storage adopts a tree structure, the upper and lower relationships among hospitals are obvious and extensible, and the inheritance configuration can set a plurality of inheritance modes such as all inheritance modes, all inheritance modes according to requirements, all independent modes and the like. Each institution can maintain own term knowledge, can inherit the term knowledge of a superior institution, inherits all the term knowledge of the superior institution when configured to be inherited in full, inherits only part of the term knowledge of the superior institution when configured to be inherited as required, and is independent from the term knowledge of a father institution when configured to be independent in full. The knowledge inheritance of multiple mechanisms greatly improves the expansibility and flexibility of the system although the processing logic is complex.

In this disclosure example, the CDSS front-end system and the CDSS integrated platform are updated, and in this example, a dynamic rendering mechanism is used to render a front-end interface, that is, the front-end interface may be dynamically rendered according to a summary (schema) component returned by a back-end, the CDSS front-end page is componentized and configured, the back-end returns API data and the schema component to the front-end, and the front-end page dynamically loads the component, and renders according to the component type. Therefore, under the condition of updating, platform operators of a front end or a target hospital are not required to be manually updated, the workload of the front end operators is less, or the front end operators hardly participate in development, only little development manpower is needed to be input, the front end joint debugging time and the rear end joint debugging time are saved, and the iteration efficiency of the whole system is greatly improved.

In a specific example, the CDSS front-end system has a plurality of product lines such as a standard edition, a basic edition, reasonable medication, and the like, and each product line needs a background management platform after being landed, wherein the product lines have independent functions and general functions, and each product line can use the same set of medical knowledge. The disclosed example can realize the function module fusion of multiple product lines of the CDSS front-end system, the back end of the platform adopts a configuration file mode, and each product line has own configuration file, for example, in one example, as shown in fig. 6, a module (or a unit, the same as the later) a module a, a module B and a module C are required to be configured by the front-end system standard version of the target hospital; the basic edition needs to be configured with a module B, a module C and a module D; the reasonable medicine layout needs to be configured with a module E and a module F; the medical records quality control needs to be configured with a module A and a module E, and then the back end fuses the modules under the configuration files of each product line before loading the system configuration, and all the modules required to be provided for the CDSS integrated platform of the target hospital under the final configuration files comprise: module a, module B, module C, module D, module E, module F.

Still referring to fig. 6, the final returned system configuration of the cdss platform is a component in which the integrated configuration files (including the module a, the module B, the module C, the module D, the module E, and the module F) of the standard edition, the basic edition, the rational medication, the medical records and the like are fused with the existing system configuration in the Mongo database to obtain the display interface again, so that the system configuration can be flexibly increased, and if a new module is added to a certain product line, only a functional module needs to be added under the corresponding configuration file. The unified management and the on-demand distribution of the CDSS system can be realized through the method, and the integrated platform can be well adapted no matter whether the currently deployed CDSS is a standard version or a basic version, so that the delivery standardization is improved.

In the disclosed example, the rights of the medical staff member are related to the account hierarchy set in the CDSS. The users of the CDSS integrated platform can have three roles altogether: supervisors, administrators, and general users. In one specific implementation, the super administrator may be set to have and have only one, and this role has no service rights and is only used for performing system level operations such as personnel management, system configuration, license initialization, knowledge inheritance configuration, and the like.

In another specific example, as shown in fig. 7, the account system adopted by the CDSS integrated platform is in a tree structure, and a super administrator can create an administrator and a common user, and the administrator can also create the administrator and the common user, and the common user has no authority for personnel management. The administrator has management rights such as deletion and modification to all lower levels under the own rights tree. For example, the administrator B may manage the administrator B1, the administrator B2, the administrator B3, the general user B31, the administrator B311, and the administrator B31 may manage only the administrator B311. If the administrator B is deleted, the administrator B1, the administrator B2, the administrator B3 and all subordinates thereof can be continuously hung under the super administrator according to the original authority, and the whole personnel tree can not be disconnected by a person in the middle of deletion. The service authority of the user is endowed to the next level through a super administrator, the authority of the lower level user cannot exceed the authority possessed by the upper level, the authority which the upper level user does not have cannot be endowed to the lower level user, and when a certain authority of the upper level user is deleted, all users under the authority tree delete the authority. The tree structure design can ensure that the authority of the platform is used to be minimized, and redundant authorities are avoided.

In one implementation manner, considering that a medical institution deploying a standard version of the CDSS front-end system needs to improve the rating capability of the electronic medical record, a medical institution deploying a basic version of the CDSS front-end system needs to check the CDSS service condition of each medical point in the area, so that the platform integrates the standard version BI and the basic version BI, and meets the requirements of different product lines through the standard version BI and the basic version BI respectively, as shown in fig. 8, the information such as the proportion, the change trend and the like can be expressed by carrying out analysis statistics on logs on various statistical charts at different times. The CDSS system writes operations into a central control log when performing various diagnosis quality control and doctor advice quality control, an offline analysis log script analyzes the log of the current day once at regular intervals (for example, 5 minutes and the like), results of statistical indexes generated by logically processing data generated in a certain time interval are written into the ES, and a CDSS integrated platform directly reads the results of the ES and displays the results on the platform. In addition, the CDSS integrated platform also has various offline tools to ensure the problem of BI historical data caused by server migration, faults and the like, and ensure the delivery stability.

By carrying out knowledge disambiguation contrast through the disclosed examples, the disambiguation algorithm solves the problem of confusion of term codes, maps the knowledge generated based on the medical knowledge graph to the hospital term, and has uniqueness. Meanwhile, management of different versions of knowledge can be realized: knowledge data change can be managed through the JSON Patch component, and operations can be recorded, so that the difficulty of incremental update is solved.

Multi-organization knowledge inheritance by way of example of the present disclosure: the large number of knowledge dimensions such as medicines support a plurality of institutions in the area, support knowledge inheritance configuration, and realize SaaS (Software as a Service) upgrading of CDSS.

The dynamic rendering mechanism exemplified by the present disclosure may improve item iteration efficiency. Because the platform page adopts a dynamic rendering mechanism, the front end performs dynamic rendering according to the schema component returned by the back end, the components are multiplexed, only incremental development is needed, the manpower input in front-end development is reduced, and the project iteration efficiency is greatly improved.

Through the multi-product line module fusion in the disclosed example, the functional modules of the CDSS product lines are combined together and are managed uniformly, distribution is performed as required during delivery, the delivery standardization is improved, and personalized customization for different product lines is not needed.

By performing rights control through the disclosed examples, the CDSS integrated platform severely limits system function allocation and personnel rights. The CDSS integrated platform can be used after being initialized through License authorization, and the authority of platform personnel is endowed by the upper personnel layer by layer, so that the platform functions cannot be used in an overriding mode.

In addition, the CDSS platform of the disclosed example also supports statistics of data generated by CDSS services and generates a visual report, covers indexes of all services such as CDSS standard edition, basic edition and reasonable medication, and can be used as important standards of hospital ratings.

In this embodiment, a certain contribution can be made to quality control of medical behaviors, a certain problem is found, and quality of diagnostic information generation such as medical advice is improved.

The embodiment of the disclosure also provides an information generating device, as shown in fig. 9, including:

a knowledge information obtaining module 91, configured to generate an instruction according to the received diagnostic information, and obtain corresponding knowledge information;

the knowledge determination module 92 is configured to determine knowledge that needs to be reminded when generating the diagnostic information according to the diagnostic information generation instruction in the knowledge information;

the reminding information generating module 93 is configured to generate reminding information according to knowledge required to be reminded.

In one embodiment, as shown in fig. 10, the knowledge determination module includes:

the first determining unit 101 is configured to, when diagnostic information corresponding to the diagnostic information generating instruction conflicts with first target knowledge information in the knowledge information, use the first target knowledge information as knowledge to be reminded.

In one embodiment, as shown in fig. 11, the knowledge determination module includes:

the second determining unit 111 is configured to, when the diagnostic information to be generated by the diagnostic information generating instruction does not include any notice required for the second target knowledge information in the knowledge information, regard the second target knowledge information as knowledge to be reminded.

In one embodiment, the knowledge information includes at least one of:

medical first knowledge information of a target hospital for a patient visit;

patient information extracted from patient history diagnostic information;

patient information autonomously provided by the patient;

second knowledge information obtained from the knowledge inheritance hospital of the target hospital; the knowledge inheritance hospital is a hospital that can share the second knowledge information to the target hospital.

In an embodiment, in a case where the knowledge information includes medical first knowledge information of a target hospital for a patient visit, as shown in fig. 12, the information generating apparatus further includes:

an autonomous knowledge module 121 for acquiring autonomous medical knowledge information of a target hospital, the autonomous medical knowledge information including autonomous terms used inside the target hospital;

the association module 122 is configured to associate the autonomous term with a generic term in the generic medical knowledge information to obtain an association result;

the first knowledge information module 123 is configured to use the association result, the autonomous medical knowledge information, and the general medical knowledge information as the first knowledge information.

In one embodiment, the knowledge information includes knowledge information generated for original knowledge fields recorded from original files in the repository and/or knowledge field updates recorded from patch files of the original files.

In one embodiment, the diagnostic information generation instructions include instructions received by controlling a presentation interface, the generation process of the presentation interface including the steps of:

generating a front-end display assembly according to the customization information of the target hospital;

and generating a display interface according to the front-end display component.

In one embodiment, the presentation interface includes a presentation item for receiving diagnostic information generation instructions; as shown in fig. 13, the information generating apparatus further includes:

the permission determining module 131 is configured to determine login permission according to information of a login person logging in the display interface, where the login permission includes a default permission corresponding to an identity of the login person and a permission authorized by an authorizer of the login person;

the display item module 132 is configured to determine a display item according to the login rights.

In one embodiment, the generating process of the display interface includes generating a front-end display component according to the customization information of the target hospital, including:

according to the customization information of the target hospital, determining the sub-components required by each section respectively;

determining a total set of sub-components required by a target hospital according to the sub-components required by each section;

and generating a front-end display component according to the sub-component total set and the basic configuration corresponding to the target hospital.

The embodiment of the disclosure can be applied to the artificial intelligence fields such as big data, knowledge graph, artificial intelligence medical treatment and the like.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related user personal information all conform to the regulations of related laws and regulations, and the public sequence is not violated.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

Fig. 15 shows a schematic block diagram of an example electronic device 150 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 15, the apparatus 150 includes a computing unit 151 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 152 or a computer program loaded from a storage unit 158 into a Random Access Memory (RAM) 153. In the RAM 153, various programs and data required for the operation of the device 150 can also be stored. The computing unit 151, ROM 152, and RAM 153 are connected to each other by a bus 154. An input/output (I/O) interface 155 is also connected to bus 154.

Various components in the device 150 are connected to the I/O interface 155, including: an input unit 156 such as a keyboard, a mouse, etc.; an output unit 157 such as various types of displays, speakers, and the like; a storage unit 158 such as a magnetic disk, an optical disk, or the like; and a communication unit 159 such as a network card, modem, wireless communication transceiver, etc. The communication unit 159 allows the device 150 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunications networks.

The computing unit 151 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 151 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 151 performs the respective methods and processes described above, for example, an information generation method. For example, in some embodiments, the information generation method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 158. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 150 via the ROM 152 and/or the communication unit 159. When a computer program is loaded into RAM 153 and executed by computing unit 151, one or more steps of the information generating method described above may be performed. Alternatively, in other embodiments, the computing unit 151 may be configured to perform the information generating method by any other suitable means (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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 foregoing.

To provide for interaction with a user, the systems and techniques described here 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 a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end 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: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims (14)

1. An information generation method, comprising:

generating an instruction according to the received diagnosis information, and acquiring corresponding knowledge information;

when diagnosis information corresponding to the diagnosis information generation instruction conflicts with first target knowledge information in the knowledge information, the first target knowledge information is used as knowledge to be reminded; and/or, in the case that the diagnostic information to be generated by the diagnostic information generation instruction does not include the notice required by the second target knowledge information in the knowledge information, using the second target knowledge information as the knowledge required to be reminded;

Generating reminding information according to the knowledge to be reminded;

wherein, in case the knowledge information comprises medical first knowledge information of a target hospital of a patient visit, the method further comprises:

acquiring autonomous medical knowledge information of a target hospital, wherein the autonomous medical knowledge information comprises autonomous terms used in the target hospital;

associating the autonomous terms with the general terms in the general medical knowledge information to obtain an association result;

and taking the association result, the autonomous medical knowledge information and the general medical knowledge information as the first knowledge information.

2. The method of claim 1, wherein the knowledge information comprises at least one of:

patient information extracted from patient history diagnostic information;

patient information autonomously provided by the patient;

second knowledge information obtained from the knowledge inheritance hospital of the target hospital; the knowledge inheritance hospital is a hospital capable of sharing second knowledge information to the target hospital.

3. The method according to claim 1 or 2, wherein the knowledge information comprises knowledge information generated for original knowledge fields recorded from original files in a repository and/or knowledge field update content recorded from patch files of original files.

4. The method of claim 1 or 2, wherein the diagnostic information generation instructions include instructions received by controlling a presentation interface, the generation process of the presentation interface comprising the steps of:

generating a front-end display assembly according to the customization information of the target hospital;

and generating the display interface according to the front-end display assembly.

5. The method of claim 4, wherein the presentation interface comprises a presentation item for receiving the diagnostic information generation instruction; the method further comprises the steps of:

determining login rights according to information of a login person logging in the display interface, wherein the login rights comprise default rights corresponding to the identity of the login person and rights authorized by an authorizer of the login person;

and determining the display item according to the login authority.

6. The method of claim 4, wherein the generating a front-end presentation component from the customization information of the target hospital comprises:

according to the customization information of the target hospital, determining the sub-components required by each section respectively;

determining a total set of sub-components required by the target hospital according to the sub-components required by each edition;

And generating a front-end display component according to the sub-component total set and the basic configuration corresponding to the target hospital.

7. An information generating apparatus comprising:

the knowledge information acquisition module is used for generating an instruction according to the received diagnosis information to acquire corresponding knowledge information;

the knowledge determination module is used for taking the first target knowledge information as knowledge to be reminded when the diagnosis information corresponding to the diagnosis information generation instruction conflicts with the first target knowledge information in the knowledge information; and/or, in the case that the diagnostic information to be generated by the diagnostic information generation instruction does not include the notice required by the second target knowledge information in the knowledge information, using the second target knowledge information as the knowledge required to be reminded;

the reminding information generation module is used for generating reminding information according to the knowledge required to be reminded; wherein, in case the knowledge information comprises medical first knowledge information of a target hospital of a patient visit, the apparatus further comprises:

the autonomous knowledge module is used for acquiring autonomous medical knowledge information of a target hospital, wherein the autonomous medical knowledge information comprises autonomous terms used in the target hospital;

The association module is used for associating the autonomous terms with the general terms in the general medical knowledge information to obtain an association result;

and the first knowledge information module is used for taking the association result, the autonomous medical knowledge information and the general medical knowledge information as the first knowledge information.

8. The apparatus of claim 7, wherein the knowledge information comprises at least one of:

patient information extracted from patient history diagnostic information;

patient information autonomously provided by the patient;

second knowledge information obtained from the knowledge inheritance hospital of the target hospital; the knowledge inheritance hospital is a hospital capable of sharing second knowledge information to the target hospital.

9. The apparatus of claim 7 or 8, wherein the knowledge information comprises knowledge information generated for original knowledge fields recorded from original files in a repository and/or knowledge field update content recorded from patch files of original files.

10. The apparatus of claim 7 or 8, wherein the diagnostic information generation instructions include instructions received by controlling a presentation interface, the presentation interface generation process comprising the steps of:

Generating a front-end display assembly according to the customization information of the target hospital;

and generating the display interface according to the front-end display assembly.

11. The apparatus of claim 10, wherein the presentation interface comprises a presentation item for receiving the diagnostic information generation instruction; the apparatus further comprises:

the permission determination module is used for determining login permission according to the information of a login person logging in the display interface, wherein the login permission comprises default permission corresponding to the identity of the login person and permission authorized by an authorizer of the login person;

and the display item module is used for determining the display item according to the login authority.

12. The apparatus of claim 10, wherein the generating of the presentation interface includes generating a front-end presentation component from the target hospital customization information, comprising:

according to the customization information of the target hospital, determining the sub-components required by each section respectively;

determining a total set of sub-components required by the target hospital according to the sub-components required by each edition;

and generating a front-end display component according to the sub-component total set and the basic configuration corresponding to the target hospital.

13. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

14. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-6.

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