Traditional Chinese medicine and western medicine combined clinical decision support system and method

Abstract

The invention discloses a traditional Chinese and western medicine combined clinical decision support system and method, and relates to the technical field of medical equipment, the system comprises a user interface module, a data management module, a knowledge base module, a rule engine module and a decision analysis module, the user interface module is used for obtaining patient information input by a clinician; the data management module is used for performing data cleaning and Chinese and western medicine medical term mapping processing on the patient information; the knowledge base module is used for tracking and updating medical knowledge and diagnosis and treatment guidelines in real time; the rule engine module is used for establishing a medical diagnosis and treatment rule base according to the medical knowledge and the diagnosis and treatment guide, calling a corresponding medical diagnosis and treatment rule from the medical diagnosis and treatment rule base according to the processed patient information, and generating a preliminary diagnosis result and a treatment scheme; and the decision analysis module is used for further performing decision analysis and optimization to obtain a final diagnosis result and a treatment scheme. The accuracy and efficiency of medical decision making of the clinical decision support system can be improved.

Description

Technical Field

[0001] The present application relates to the field of medical equipment technology, and in particular to a clinical decision support system and method combining traditional Chinese and Western medicine. Background Art

[0002] A Clinical Decision Support System (CDSS) refers to a computer system that supports clinical decision-making. CDSSs fully utilize available and appropriate computer technologies to address semi-structured or unstructured medical problems, improving and enhancing the efficiency of clinical decision-making through human-computer interaction. They are an important means of improving healthcare quality. However, most current CDSSs for Traditional Chinese Medicine and Western medicine are relatively independent systems. For example, Traditional Chinese Medicine uses the Traditional Chinese Medicine Clinical Decision Support System (TCMCDSS), designed specifically for Traditional Chinese Medicine, while Western Medicine uses Western Medicine Clinical Decision Support Systems designed specifically for Western medicine. Consequently, there is no truly integrated clinical decision support system that integrates Traditional Chinese Medicine and Western medicine. Furthermore, most current CDSSs lack high accuracy and efficiency in medical decision-making. Summary of the Invention

[0003] The purpose of this application is to provide a clinical decision support system and method that integrates traditional Chinese and Western medicine, which can improve the accuracy and efficiency of medical decision-making in the clinical decision support system.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a clinical decision support system for integrating traditional Chinese and Western medicine, the clinical decision support system comprising a user interface module, a data management module, a knowledge base module, a rule engine module, and a decision analysis module; the user interface module is respectively connected to the data management module, the knowledge base module, the rule engine module, and the decision analysis module; the rule engine module is further respectively connected to the data management module and the knowledge base module; and the decision analysis module is further respectively connected to the data management module, the knowledge base module, and the rule engine module;

[0006] The user interface module is used to obtain patient information input by a clinician and transmit the patient information to the data management module, wherein the patient information includes patient personal information, disease symptoms and examination results;

[0007] The data management module is used to store the patient information, perform data cleaning and mapping of Chinese and Western medical terms on the patient information to obtain processed patient information, and transmit the processed patient information to the rule engine module; the mapping of Chinese and Western medical terms is used to ensure consistency between Chinese and Western medical terms;

[0008] The knowledge base module is used to store medical knowledge and diagnosis and treatment guidelines, track and update the medical knowledge and diagnosis and treatment guidelines in real time, and transmit the latest medical knowledge and diagnosis and treatment guidelines to the rule engine module; the medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavior guidelines related to medical diagnosis and treatment of traditional Chinese medicine and Western medicine;

[0009] The rule engine module is used to establish a medical diagnosis and treatment rule library based on the medical knowledge and diagnosis and treatment guidelines, and retrieve corresponding medical diagnosis and treatment rules from the medical diagnosis and treatment rule library based on the processed patient information, generate preliminary diagnosis results and treatment plans based on the medical diagnosis and treatment rules, and transmit the preliminary diagnosis results and treatment plans to the decision analysis module; the medical diagnosis and treatment rule library includes a plurality of medical diagnosis and treatment rules, each of which includes the name of a disease, disease symptoms and corresponding diagnosis results and treatment plans;

[0010] The decision analysis module is used to perform decision analysis and optimization on the preliminary diagnosis results and treatment plans to obtain the final diagnosis results and treatment plans.

[0011] Optionally, the user interface module includes a user input unit, a human-computer interaction unit and a user interface display unit;

[0012] The user input unit is used to receive the patient information input by the clinician and transmit the patient information to the data management module;

[0013] The human-computer interaction unit is used for human-computer interaction between the clinician and the system;

[0014] The user interface display unit is used to visually display the final diagnosis result and treatment plan.

[0015] Optionally, the data management module includes a data storage unit and a data cleaning and preprocessing unit;

[0016] The data storage unit is used to store the patient information;

[0017] The data cleaning and preprocessing unit is used to clean the patient information, establish a virtual case based on the patient information after data cleaning, and perform Chinese and Western medicine medical terminology mapping processing based on the patient information after data cleaning and the virtual case to obtain the processed patient information, and transmit the processed patient information to the rule engine module.

[0018] Optionally, the knowledge base module includes a knowledge entry unit and a knowledge update unit;

[0019] The knowledge input unit is used to input and store the medical knowledge and diagnosis and treatment guidelines;

[0020] The knowledge updating unit is used to track and update the medical knowledge and diagnosis and treatment guidelines in real time, and transmit the latest medical knowledge and diagnosis and treatment guidelines to the rule engine module.

[0021] Optionally, the rule engine module includes a rule base management unit and a rule base execution engine unit;

[0022] The rule base management unit is used to establish a medical diagnosis and treatment rule base based on the medical knowledge and diagnosis and treatment guidelines, and to perform management operations on the medical diagnosis and treatment rules in the medical diagnosis and treatment rule base, wherein the management operations include adding medical diagnosis and treatment rules, modifying medical diagnosis and treatment rules, and deleting medical diagnosis and treatment rules;

[0023] The rule base execution engine unit is used to dynamically load diagnosis and treatment rules and matching decision models, and according to the processed patient information, use the diagnosis and treatment rules and matching decision models to parse the processed patient information and all medical diagnosis and treatment rules, and retrieve the medical diagnosis and treatment rules corresponding to the processed patient information from the medical diagnosis and treatment rule base, generate preliminary diagnosis results and treatment plans according to the medical diagnosis and treatment rules, and transmit the preliminary diagnosis results and treatment plans to the decision analysis module; the diagnosis and treatment rules and matching decision model is a model established based on disease symptoms and medical diagnosis and treatment rules, and is used to match corresponding medical diagnosis and treatment rules according to the disease symptoms in the patient information.

[0024] Optionally, the decision analysis module includes a machine learning unit and a decision analysis unit;

[0025] The machine learning unit is used to analyze and learn historical data using machine learning technology to improve the decision-making performance of the decision analysis unit; the historical data includes historical patient information and corresponding historical diagnosis results and historical treatment plans;

[0026] The decision analysis unit is used to perform comprehensive comparison and decision analysis based on the preliminary diagnosis results and treatment plans and the historical data to obtain the final diagnosis results and treatment plans.

[0027] Optionally, the clinical decision support system integrating traditional Chinese and western medicine further comprises a report output module, which is connected to the decision analysis module and the user interface module respectively, and comprises a report analysis unit and a report display unit;

[0028] The report analysis unit is used to generate a diagnosis and treatment report based on the final diagnosis result and treatment plan;

[0029] The report display unit is used to transmit the diagnosis and treatment report to the user interface module for visual display.

[0030] Optionally, the report analysis unit uses Jasper Reports or Crystal Reports report generation tools.

[0031] Optionally, the clinical decision support system integrating traditional Chinese and Western medicine is provided with a mediator pattern, which constructs a mediator chain of many-to-many components in the form of multiple mediators, and the mediator chain is used to coordinate the communication between the user interface module, the data management module, the knowledge base module, the rule engine module and the decision analysis module.

[0032] In a second aspect, the present application provides a clinical decision support method integrating traditional Chinese and Western medicine, the clinical decision support method integrating traditional Chinese and Western medicine comprising:

[0033] Obtaining patient information, including patient personal information, disease symptoms, and examination results;

[0034] Performing data cleaning and mapping of Chinese and Western medical terms on the patient information to obtain processed patient information; the mapping of Chinese and Western medical terms is used to ensure consistency between Chinese and Western medical terms;

[0035] Based on the processed patient information, the corresponding medical diagnosis and treatment rules are retrieved from a medical diagnosis and treatment rule library, and a preliminary diagnosis result and treatment plan are generated based on the medical diagnosis and treatment rules; the medical diagnosis and treatment rule library is a database including a plurality of medical diagnosis and treatment rules established based on medical knowledge and diagnosis and treatment guidelines, wherein the medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavior guidelines related to medical diagnosis and treatment of traditional Chinese medicine and Western medicine, and each medical diagnosis and treatment rule includes the name of a disease, disease symptoms, and corresponding diagnosis results and treatment plan;

[0036] Perform decision analysis and optimization on the preliminary diagnosis results and treatment plans to obtain final diagnosis results and treatment plans.

[0037] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0038] This application provides a clinical decision support system and method for integrating traditional Chinese medicine and Western medicine. The system obtains patient information input by a clinician through a user interface module, and then performs data cleaning and mapping of traditional Chinese and Western medical terminology on the patient information through a data management module, thereby ensuring the accuracy of the patient information and the consistency between traditional Chinese and Western medical terminology. This system preliminarily achieves the integration and adaptation of traditional Chinese medicine and Western medicine in a clinical decision support system. Furthermore, the system integrates the real-time updated medical knowledge and treatment guidelines of traditional Chinese medicine and Western medicine provided by a knowledge base module, and uses a rule engine module to establish a medical diagnosis and treatment rule library, retrieve the medical diagnosis and treatment rules corresponding to the patient information, thereby obtaining preliminary diagnosis results and treatment plans. Further decision analysis and optimization are then performed through a decision analysis module to obtain the final diagnosis results and treatment plans. Therefore, this application achieves the integration of traditional Chinese medicine and Western medicine in terms of medical terminology, medical knowledge, and treatment guidelines, making the clinical decision support system for integrating traditional Chinese medicine and Western medicine applicable to both traditional Chinese medicine and Western medicine. Furthermore, this application integrates multiple information such as patient information, medical knowledge, treatment guidelines, and medical diagnosis and treatment rules to make diagnostic decisions, which can effectively improve the accuracy of the system. By using rule engine technology, medical diagnosis and treatment rules corresponding to patient information can be quickly retrieved, so that diagnosis results and treatment plans can be quickly obtained, thereby effectively improving the accuracy and work efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0040] Figure 1 A schematic diagram of the structure of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0041] Figure 2 A flowchart of a clinical decision support method combining traditional Chinese and Western medicine provided in one embodiment of the present application.

[0042] Figure 3 This is a basic architecture diagram of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0043] Figure 4 A server architecture diagram of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0044] Figure 5This is a software architecture diagram of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0045] Figure 6 A flowchart of calling data for a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0046] Figure 7 This is a hardware architecture diagram of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0047] Figure 8 This is a structural diagram of the comprehensive analysis module of the clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application.

[0048] Figure 9 This is a diagram of the rule engine architecture of a clinical decision support system integrating traditional Chinese and Western medicine provided in one embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0050] like Figure 1 As shown, this embodiment proposes a clinical decision support system integrating traditional Chinese and Western medicine. The system mainly includes functional modules such as a user interface module, a data management module, a knowledge base module, a rule engine module, and a decision analysis module. The user interface module is connected to the data management module, the knowledge base module, the rule engine module, and the decision analysis module respectively. The rule engine module is further connected to the data management module and the knowledge base module respectively. The decision analysis module is further connected to the data management module, the knowledge base module, and the rule engine module respectively.

[0051] The user interface module is used to obtain patient information input by clinicians and transmit the patient information to the data management module. Patient information includes patient personal information, disease symptoms, and examination results. The data management module is used to store patient information, perform data cleaning and mapping of Chinese and Western medical terminology to obtain processed patient information, and transmit the processed patient information to the rule engine module; the Chinese and Western medical terminology mapping process is used to ensure consistency between Chinese and Western medical terminology. The knowledge base module is used to store medical knowledge and diagnosis and treatment guidelines, track and update medical knowledge and diagnosis and treatment guidelines in real time, and transmit the latest medical knowledge and diagnosis and treatment guidelines to the rule engine module; medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavioral guidelines related to Chinese and Western medical diagnosis and treatment. The rule engine module is used to establish a medical diagnosis and treatment rule library based on medical knowledge and diagnosis and treatment guidelines. It then retrieves the corresponding medical diagnosis and treatment rules from the medical diagnosis and treatment rule library based on processed patient information, generates preliminary diagnosis results and treatment plans based on the medical diagnosis and treatment rules, and transmits these preliminary diagnosis results and treatment plans to the decision analysis module. The medical diagnosis and treatment rule library includes several medical diagnosis and treatment rules, each of which includes the name of a disease, disease symptoms, and corresponding diagnosis results and treatment plans. The decision analysis module is used to perform decision analysis and optimization on the preliminary diagnosis results and treatment plans to obtain the final diagnosis results and treatment plans.

[0052] In this embodiment, the user interface module includes a user input unit, a human-computer interaction unit and a user interface display unit, wherein the user input unit is used to receive patient information input by the clinician and transmit the patient information to the data management module; the human-computer interaction unit is used for human-computer interaction between the clinician and the system; and the user interface display unit is used to visualize the final diagnosis results and treatment plan.

[0053] In this embodiment, the data management module includes a data storage unit and a data cleaning and preprocessing unit, wherein the data storage unit is used to store patient information; the data cleaning and preprocessing unit is used to clean the patient information, establish a virtual case based on the cleaned patient information, and perform Chinese and Western medicine medical terminology mapping processing based on the cleaned patient information and the virtual case to obtain the processed patient information, and transmit the processed patient information to the rule engine module.

[0054] In this embodiment, the knowledge base module includes a knowledge entry unit and a knowledge update unit, wherein the knowledge entry unit is used to enter and store medical knowledge and treatment guidelines; the knowledge update unit is used to track and update medical knowledge and treatment guidelines in real time, and transmit the latest medical knowledge and treatment guidelines to the rule engine module.

[0055] In this embodiment, the rule engine module includes a rule base management unit and a rule base execution engine unit, wherein the rule base management unit is used to establish a medical diagnosis and treatment rule base based on medical knowledge and diagnosis and treatment guidelines, and perform management operations on the medical diagnosis and treatment rules in the medical diagnosis and treatment rule base, and the management operations include adding medical diagnosis and treatment rules, modifying medical diagnosis and treatment rules, and deleting medical diagnosis and treatment rules; the rule base execution engine unit is used to dynamically load diagnosis and treatment rules and matching decision models, and according to the processed patient information, use the diagnosis and treatment rules and matching decision models to parse the processed patient information and all medical diagnosis and treatment rules, and retrieve the medical diagnosis and treatment rules corresponding to the processed patient information from the medical diagnosis and treatment rule base, generate preliminary diagnosis results and treatment plans according to the medical diagnosis and treatment rules, and transmit the preliminary diagnosis results and treatment plans to the decision analysis module; the diagnosis and treatment rules and matching decision model is a model established based on disease symptoms and medical diagnosis and treatment rules, and is used to match corresponding medical diagnosis and treatment rules according to the disease symptoms in the patient information.

[0056] In this embodiment, the decision analysis module includes a machine learning unit and a decision analysis unit, wherein the machine learning unit is used to analyze and learn historical data using machine learning technology to improve the decision-making performance of the decision analysis unit; historical data includes historical patient information and corresponding historical diagnosis results and historical treatment plans; the decision analysis unit is used to conduct comprehensive comparison and decision analysis based on preliminary diagnosis results and treatment plans and historical data to obtain the final diagnosis results and treatment plans.

[0057] In this embodiment, the clinical decision support system integrating traditional Chinese and Western medicine also includes a report output module, which is connected to the decision analysis module and the user interface module respectively. The report output module includes a report analysis unit and a report display unit; the report analysis unit is used to generate a diagnosis and treatment report based on the final diagnosis results and treatment plan; the report display unit is used to transmit the diagnosis and treatment report to the user interface module for visual display.

[0058] In this embodiment, the report analysis unit adopts Jasper Reports or Crystal Reports report generation tools.

[0059] In this embodiment, the clinical decision support system combining traditional Chinese and Western medicine is provided with a mediator pattern. The mediator pattern constructs a mediator chain of many-to-many components in the form of multiple mediators. The mediator chain is used to coordinate the communication between the user interface module, the data management module, the knowledge base module, the rule engine module and the decision analysis module.

[0060] In an exemplary embodiment, a clinical decision support method for integrating traditional Chinese and Western medicine is provided. The method corresponds to a clinical decision support system for integrating traditional Chinese and Western medicine. Figure 2 As shown, the method specifically includes the following steps:

[0061] Step S1: Obtain patient information, which includes patient personal information, disease symptoms, and examination results.

[0062] Step S2: perform data cleaning and mapping of Chinese and Western medical terms on the patient information to obtain processed patient information; the mapping of Chinese and Western medical terms is used to ensure consistency between Chinese and Western medical terms.

[0063] Step S3: Based on the processed patient information, the corresponding medical diagnosis and treatment rules are retrieved from the medical diagnosis and treatment rule library, and a preliminary diagnosis result and treatment plan are generated based on the medical diagnosis and treatment rules; the medical diagnosis and treatment rule library is a database including several medical diagnosis and treatment rules established based on medical knowledge and diagnosis and treatment guidelines. Medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavioral guidelines related to traditional Chinese medicine and Western medicine. Each medical diagnosis and treatment rule includes the name of a disease, disease symptoms and corresponding diagnosis results and treatment plan.

[0064] Step S4: Analyze and optimize the preliminary diagnosis results and treatment plans to obtain the final diagnosis results and treatment plans.

[0065] In order to make the technical solution of this embodiment clearer, the basic architecture and detailed structure of the clinical decision support system combining traditional Chinese and Western medicine in this embodiment, as well as the specific implementation process of the clinical decision support method combining traditional Chinese and Western medicine, are described below in the form of examples.

[0066] The clinical decision support system for combining traditional Chinese and Western medicine proposed in this embodiment is a knowledge-based clinical decision support system applicable to both traditional Chinese and Western medicine. Figure 3 The basic architecture of this integrated Chinese and Western medicine clinical decision support system is shown, primarily comprising a data center, knowledge base, data acquisition system, inference engine, interpreter, and user interface. The knowledge base obtains patient information from the data center, and the data acquisition system then uses it to acquire medical knowledge and treatment guidelines pre-entered by knowledge engineers. This facilitates the establishment of a medical diagnosis and treatment rule library containing several medical diagnosis and treatment rules. The interpreter-based inference engine then performs inferences, presenting the results to the user through the user interface. Figure 4The server architecture is shown. The servers of the clinical decision support system integrating traditional Chinese and Western medicine mainly include terminal servers, Web servers, file servers, application servers, database servers and other servers. Among them, terminal servers and Web servers are mainly used to build cloud architecture, cloud storage and cloud computing, while other servers are used for interaction with other devices, applications, etc. and data processing.

[0067] The design contents of the clinical decision support system integrating traditional Chinese and Western medicine at different design stages are as follows:

[0068] Step 1: System software solution design phase.

[0069] In the system software design phase, the software development of the clinical decision support system for integrated Chinese and Western medicine in this embodiment mainly focuses on the data integration and processing system with the database as the core, the design and optimization of decision support algorithms based on machine learning and artificial intelligence, as well as support for personalized settings and operation processes, and the design of an intuitive and easy-to-use user interface, which is used by users such as clinicians and clinical workers, such as Figure 5 shown.

[0070] In this embodiment, when constructing a stable system architecture of a clinical decision support system integrating traditional Chinese and Western medicine, in order to ensure the stability, scalability and flexibility of the system, the database storage content of the clinical decision support system integrating traditional Chinese and Western medicine includes clinical data, patient information, treatment plans, etc. Figure 6 As shown in the figure, through the processes of multi-source data integration, data cleaning, data call and data integration output, data quality and consistency are ensured to meet clinical needs and actual application scenarios. The user interface adopts graphical display and intelligent recommendation functions to facilitate clinicians to view diagnostic results, give suggestions and interactive operations. In addition, the business domains between various modules of the overall clinical decision-making business are encapsulated and upgraded for user operations, becoming a flexible and configurable interface to achieve seamless knowledge base, reasoning engine and human-computer communication interface. The reasoning engine is an engine for integrating, comparing and analyzing knowledge base knowledge and patient information. Clinicians, as the end users, need to participate in the CDSS rules, design and development, as well as the actual test feedback and targeted optimization of related modules after the system is launched.

[0071] The basic modules of the clinical decision support system for integrating traditional Chinese and Western medicine in this embodiment are as follows:

[0072] The user interface module includes a user input unit, a human-computer interaction unit, and a user interface display unit. The data management module includes a data storage unit, a data cleaning and preprocessing unit. The knowledge base module includes a knowledge entry unit and a knowledge update unit. The rule engine module includes a rule base management unit and a rule base execution engine unit. The decision analysis module includes a decision analysis unit and a machine learning unit. The report output module includes a report analysis module and a report display module.

[0073] The user interface module provides clinicians with an interactive interface for entering patient information and viewing system recommendations. Accessing patient medical information from the database facilitates easy interaction with the system. The data management module stores patient clinical data, test results, diagnoses, and other information. The decision analysis module utilizes a mediator pattern, introducing mediator objects when connecting components to the communication network, transforming communication between components into an indirect method. This event-driven system features multiple mediators, with a chain of mediators between them. When exchanging, storing, and transmitting data, components do not directly access the database. Instead, they send events to the mediator, which triggers the corresponding data interaction actions, such as data transmission, access, and storage. The decision analysis module also handles message delivery and collaborative control among the modules. The knowledge base module provides automatic updates and manual entry of information related to integrated traditional Chinese and Western medicine, disease diagnosis and treatment protocols, and drug information. This includes self-built knowledge bases for genomics and bioinformatics. The rule engine module infers and makes decisions based on the patient's clinical information and rules in the knowledge base, assisting clinicians in developing treatment plans. Medical diagnosis and treatment rules in the rule base must be invoked, and their execution requires a mediator to transmit events from objects in the rule engine component. The report output module can be used to explain the system's recommendations and decision-making basis, helping clinicians understand the system's recommendation logic. It can also display previous case reports and implemented treatment plans, enabling clinicians to comprehensively control patients from the onset to the progression of the disease.

[0074] The clinical decision support system for integrated Chinese and Western medicine in this embodiment also includes natural language processing, data organization, data tracking, and encryption and decryption algorithms for the integrated Chinese and Western medicine database based on C# and Python programming languages. When designing the knowledge base architecture, it is necessary to edit the rules of the Chinese and Western medicine knowledge base, and automatically learn and update the knowledge base rules in combination with decision support algorithms based on machine learning and artificial intelligence. Among them, the decision support algorithms based on machine learning and artificial intelligence include RNN (Recurrent Neural Network, recurrent neural network), LSTM (Long Short-Term Memory, long short-term memory network), GRU (Gate Recurrent Unit, gated recurrent unit) and other algorithms to process sequence data, combined with algorithms such as K-Means (clustering) algorithm, random forest algorithm, decision tree algorithm and rule inference algorithm, continuously meeting the computing needs of the clinical decision support system for integrated Chinese and Western medicine.

[0075] The integrated Chinese and Western medicine clinical decision support system in this embodiment can implement integrated Chinese and Western medicine diagnosis, treatment recommendations, and drug recommendations. Furthermore, in application scenarios, it can communicate and collaborate with clinicians and experts in real time, understand the treatment plans and prognosis plans selected by clinicians and experts in integrated Chinese and Western medicine treatment, and implement the function of generating and recommending personalized diagnosis and treatment plans. For example, the integrated Chinese and Western medicine clinical decision support system also includes a comprehensive analysis module that can automatically integrate Chinese and Western medicine medical record data, including disease symptom descriptions, physical signs, laboratory test results, etc., to form a comprehensive patient profile. The system is connected to the knowledge base module via a web server and uses artificial intelligence algorithms to perform auxiliary diagnosis based on patient medical record data and the latest medical knowledge base, providing a list of possible disease candidates. During clinician use, flexible human-computer interaction can be used to generate personalized Chinese and Western medicine treatment plans and provide recommendations on drug selection, dosage, and treatment course. At the same time, within the system's cloud architecture, based on standard medical record data from the hospital's existing relevant medical systems, a Chinese and Western medicine knowledge graph can be established, including disease-symptom associations and drug-disease associations, to provide knowledge retrieval and learning support for clinicians.

[0076] Step 2: System hardware design phase.

[0077] In the hardware design phase of the system, the hardware development of the clinical decision support system integrating traditional Chinese and Western medicine in this embodiment mainly involves combining the software system, designing hardware equipment, and leaving sufficient information channels in medical equipment interfaces, intelligent diagnostic instruments, etc. to achieve real-time data collection and interaction as well as hardware equipment security and privacy protection mechanisms. Figure 7As shown, the hardware of this embodiment mainly includes a host, a storage module, a communication module, a computing module, an execution module, a monitoring module, and other aspects. It also includes switches, embedded ECU (Electronic Control Unit) hardware, computing chips, and some underlying hardware that cooperates with the software engineering department to assemble new hardware devices such as data file servers, application servers, and database servers. At the same time, considering the security of the hardware equipment, advanced privacy protection mechanisms are used to ensure the safe and reliable transmission and storage of medical data, optimize the performance of the hardware equipment, and improve the data processing speed and system response time to meet the real-time needs of the clinical site.

[0078] Step 3: System development requirements determination phase.

[0079] During the system development requirements determination phase, this embodiment primarily focused on ensuring the compatibility and integration of the software and hardware systems, enabling seamless connection and collaborative work, and providing a complete clinical decision support solution. This involved integrating multi-source data, including traditional Chinese and Western medicine clinical data, medical records, and medical knowledge bases, establishing a unified data platform, and continuously optimizing the decision support algorithms for the integrated Chinese and Western medicine clinical decision support system. Data integration, algorithm design, and user interface development were systematically integrated to ensure collaborative work across modules. Subsequent system evaluation and verification involved collaboration with clinicians, collecting feedback, and optimizing the system. Continuous iteration and improvement were performed to enhance system performance and applicability.

[0080] Step 4: System development phase.

[0081] During the system development phase, this embodiment mainly develops the system back-end data processing methods and algorithms, and uses data encryption and access control mechanisms; develops the front-end user interface and interactive functions, designs a rights management system, provides data visualization functions, and displays patient information, diagnostic results, and treatment recommendations; develops the hardware assembly design and introduces a privacy protection mechanism; at the same time, ensures the information channel of the medical device interface and the intelligent diagnostic instrument interface; integrates various parts of the system, and conducts overall system testing and debugging.

[0082] Step 5: System testing and verification phase.

[0083] During the system testing and verification phase, this embodiment mainly conducts system functional tests such as unit testing, integration testing, and system testing. It also conducts user acceptance testing to obtain user feedback and make adjustments to verify the effectiveness and reliability of the system in clinical scenarios.

[0084] Step 6: System deployment and maintenance phase.

[0085] During the system deployment and maintenance phase, this embodiment mainly deploys the system into an actual clinical environment, continuously monitors system performance and data quality, and regularly updates the system to add new features and fix vulnerabilities.

[0086] The integrated Chinese and Western medicine clinical decision support system in this embodiment includes a database, a knowledge center, an inference engine, an interpreter, a user interface (client), a server (server-side), and a switch. The core component of the system architecture is the rule engine, a rule-based expert system (RBES) that primarily includes a knowledge base, a fact base, and an inference engine. The knowledge base consists of predicate calculus facts and discussion topic rules, encompassing a series of organized knowledge and rules. This knowledge is primarily sourced from the experience of practitioners in the fields of Chinese and Western medicine, academic research results, and relevant expertise from classic case summaries. The fact base stores specific event and problem information and facts. The inference engine matches the facts in the fact base with the conditional components of the rules. A pattern matcher continuously scans the fact base, searching for information combinations that meet the rule conditions. Under an agenda, if multiple rules are satisfied, the applicable agenda is determined for inference. Special decision information is used to determine the inference direction based on a specific rule sequence. Once the agenda is established, the execution engine executes the corresponding operations. A pattern matcher determines when to execute a rule, an agenda manager selects the order in which rules should be executed, and an execution engine executes rules and other actions. The knowledge center is a large-scale clinical knowledge base, centered around a decision engine that stably supports real-time computation of rules and models. It encompasses database access, interpreter execution, and inference engine execution. The switch organizes and exchanges information between the user interface (client) and the server, integrating with the internet to create a communication path accessible to ordinary users.

[0087] The clinical decision support system integrating traditional Chinese and Western medicine in this embodiment also includes multiple basic functional modules such as a user interface module, a data management module, a knowledge base module, a rule engine module and a decision analysis module.

[0088] The user interface module includes a user input unit, a human-computer interaction unit, and a user interface display unit. The user input unit receives patient information input by clinicians, including patient personal information, disease symptoms, test results, and real-time detection results of some intelligent diagnostic and treatment instruments; the human-computer interaction unit handles the interaction between the user and the system, including the parsing of user input and the display of system output; the user interface display unit ensures that clinical information is presented clearly and easily understood, and at the same time applies internal programs to visualize some data for better data presentation. The user interface module communicates with other modules through an API (Application Programming Interface) or other data exchange methods to achieve interaction between user input and system data.

[0089] In this embodiment, the data management module includes a data storage unit and a data cleaning and preprocessing unit, wherein the data storage unit is used to store and back up patient personal information, case data, medical knowledge base and other data, and establish multiple sources of data protection, that is, it is necessary to establish a stable data storage and encryption database, and develop natural language processing, data collation, data tracking, encryption and decryption, and data backup algorithms. The data cleaning and preprocessing unit is used to clean and preprocess the input data to ensure the accuracy and consistency of the data, which includes standard Chinese and Western medical terminology mapping, combined with the establishment of automated virtual medical records, to achieve automated term mapping. It is necessary to carry natural language algorithm-type text mining algorithms and entity recognition algorithms; data-type algorithms such as clustering and classification algorithms, data cleaning and preprocessing algorithms, and data filtering algorithms.

[0090] In this embodiment, the knowledge base module includes a knowledge entry unit and a knowledge update unit. The knowledge entry unit allows professionals to enter the latest medical knowledge, diagnosis and treatment guidelines, and other information. The knowledge update unit cooperates with large medical institutions to facilitate the establishment of an AI decision model library. At the same time, it realizes real-time tracking and updating of medical knowledge, regularly updates the content of the knowledge base, and ensures that the system's diagnosis and decision recommendations are based on the latest information. It is necessary to carry ontological knowledge graph algorithms and expert system algorithms of the knowledge reasoning algorithm type; decision tree algorithms, support vector machine algorithms, and neural network deep learning algorithms of the machine learning algorithm type.

[0091] In this embodiment, the rule engine module includes a rule base management unit and a rule base execution engine unit, wherein the rule base management unit includes creating a medical diagnosis and treatment rule base after classifying the static knowledge base (clinical guidelines, clinical pathways, etc.), accepting clinical facts and judging filtering, parsing and converting them into specific forms, etc., allowing rule administrators to manage the medical diagnosis and treatment rule base, including operations such as adding, modifying and deleting rules. The rule base execution engine unit can dynamically load diagnosis and treatment rules and matching decision models, parse and execute rules, and determine which diagnosis and treatment rules are satisfied and which decision scenario descriptions are met based on the input conditions and generate corresponding diagnosis and treatment recommendations. It is necessary to carry analytical algorithms such as collaborative filtering algorithms, genetic algorithms, simulation filtering algorithms, time series prediction algorithms, etc.

[0092] In this embodiment, the decision analysis module includes a decision analysis unit and a machine learning unit. The machine learning unit uses machine learning technology to analyze and learn large amounts of data to improve the system's decision accuracy and efficiency. The algorithms it carries include machine learning algorithms, analysis algorithms, etc. The decision analysis unit performs data analysis on the results generated by the rule engine module, and compares and analyzes the same type of data from multiple data sources to provide deeper insights and optimization suggestions.

[0093] The integrated Chinese and Western medicine clinical decision support system in this embodiment also includes a report output module, which includes a report analysis unit and a report display unit. The report analysis unit generates a detailed report based on the diagnosis results and decision recommendations, including a diagnosis summary, treatment plan, predicted prognosis, and other information. Report generation tools include JasperReports and Crystal Reports, and the algorithms used include knowledge reasoning algorithms and natural language processing algorithms. The report display unit displays the user interface to ensure that clinicians can quickly understand and apply the report content.

[0094] The user interface module, data management module, knowledge base module, rule engine module, and decision analysis module, among other basic functional modules, can be broadly divided into three modules: a knowledge service management module, a comprehensive analysis module, and a human-computer interaction module. The human-computer interaction module includes a knowledge base service interface and a rule engine interface, a RESTful (Representational State Transfer) interface, and a dynamic link library interface developed in C# and Python. It can return the decision engine's decisions to the HIS (Hospital Information System) and provide decision reports and real-time warnings. The knowledge base service management module is the foundation for implementing an open clinical support system integrating traditional Chinese and Western medicine. The static knowledge base contains structured knowledge and a document library. The model library is an AI decision-making model library built based on the basic data set of electronic medical records. The system supports customized clinical models to solve the complex and changeable scenario applications of the clinical system. The rule library is a medical diagnosis and treatment rule library created after static knowledge classification. Its interface methods include RESTful interface and dynamic link knowledge base service interface developed in C# and Python. As a clinical knowledge information assistant, it works together with the rule engine of the clinical decision support system for integrated Chinese and Western medicine, the HIS and EMR (Electronic Medical Record) of the medical system, and VMR (Virtual Medical Record), that is, the highly structured and standardized information model HL7V3RIM (HealthLevel 7V3 Reference Information Model, the third generation reference information model of the health information exchange standard) to create a unified information structure for the open clinical decision support system for integrated Chinese and Western medicine. This ensures that medical data from different sources and types follow relevant standards and specifications in the informatics and medical fields under a unified framework, standardizes various responsible medical information, and computerizes the information into the clinical decision support system for integrated Chinese and Western medicine, and generates corresponding decision reports through the knowledge decision engine. like Figure 8As shown, the database server includes a clinical knowledge database and an evidence-based medicine and management database. The SQL Server (Structured Query Language Server, relationship management service) database and the Redis (Remote Dictionary Server, remote dictionary service) database can be used. The SQL Server database stores static knowledge, rules, ontology elements, document lists and other data in the clinical decision support system of integrated Chinese and Western medicine, and the Redis database transfers patient clinical information and rules. This embodiment not only uses the powerful SQL Server database to ensure a multi-level security mechanism, but also can quickly switch to a backup server when a server fails; it also uses an efficient Redis database. The Redis database supports a variety of data structures, quickly responds to requests, and supports real-time data processing and caching. It is dynamically linked to the rule engine via an interface. As the core of the comprehensive analysis module, the rule engine can interact with modules such as the user interface module, data management module, knowledge base module, decision analysis module, and report output module through the rule engine API.

[0095] The detailed operational process of the integrated Chinese and Western medicine clinical decision support system of this embodiment is as follows: First, the clinician enters patient-related information through the user interface module, or preliminarily retrieves relevant auxiliary information through the hospital's HIS system. The user interface module then transmits the patient information to the data management module, where it is stored in the data storage unit. A virtual medical record is then created in the data cleaning and preprocessing unit, incorporating a series of HL7 V3 RIM model standards. The rule engine module then retrieves patient information and multi-source information from the data storage unit, including medical knowledge from a SQL Server database and medical diagnosis and treatment rules from a Redis database. The rule engine module executes the medical diagnosis and treatment rules to initially generate a diagnosis, treatment plan, and recommendations for the patient. The preliminary diagnosis results are then transmitted to the decision analysis module for further analysis and optimization. The decision analysis module then generates a final, detailed diagnosis report and decision recommendations. The report output module then sends the generated report back to the user interface module for presentation to the clinician. Finally, the clinician reviews the report, interacts with the system as needed, queries the latest clinical knowledge in real time, and further confirms, adjusts, or refines the information based on their clinical experience and judgment, ultimately generating a final diagnosis and treatment plan.

[0096] In this embodiment, the connection between the above functional modules is achieved in the following manner:

[0097] 1) Data Flow: Data flows are used to transfer information between functional modules, ensuring the circulation and sharing of information. Data computerization is clearly applied in the data cleaning and preprocessing unit, combined with the HL7V3RIM model and other standards to establish virtual medical records.

[0098] 2) Interface Design: Well-designed interfaces and standardized data formats enable communication and data exchange between different modules. Interface methods include RESTful interfaces and dynamic link knowledge base service interfaces developed in C# and Python.

[0099] 3) Event-driven: When a module's status changes, a corresponding event is triggered, notifying other modules to respond. For example, a rule engine determines that a medical diagnosis and treatment rule in a medical diagnosis and treatment rule library will be executed and generate an event.

[0100] 4) Mediator Pattern: The mediator pattern, also known as the regulator pattern or conciliator pattern, introduces the mediator pattern. This pattern coordinates communication between functional modules by building a many-to-many component mediator chain through multiple mediators. After the mediator and component objects are created and registered with the mediator, the relationship between the mediators is set to form a mediator chain. When the system sends events to components, they are transmitted to other components along the mediator chain without requiring inter-component communication. When adding or modifying mediator relationships, only the mediator chain configuration needs to be adjusted, ensuring the independence of different modules and reducing the coupling between modules. The comprehensive analysis module, to a certain extent, serves as the computing core and plays a coordinating role among the various functional modules of the system.

[0101] 5) Database Sharing: All functional modules share the same database, ensuring data consistency and real-time availability. The knowledge base not only contains static knowledge such as clinical knowledge and evidence-based medical rules, but also includes real-time input including patient information and patient-related data from multiple data sources.

[0102] The clinical decision support system combining traditional Chinese and Western medicine in this embodiment can also be divided into software and hardware parts. The hardware part includes high-performance, high-capacity, high-speed, and reliable computers, switches, high-definition, responsive displays, keyboards and mice, touch screen devices, printers and other output devices in the human-computer interaction equipment category; high-performance, high-capacity, high-speed, and reliable storage servers, data file servers, application servers, database servers, etc. in the knowledge service management equipment category; embedded ECU hardware, computing power chips and some underlying hardware; comprehensive analysis categories include some embedded devices, high-performance computing power chips and high-quality SSDs (Solid State Disks) and cloud servers, GPU (Graphics Processing Unit) acceleration cards, and high-performance servers. In terms of software, the user interface software, data management software, rule engine software, knowledge base management software, decision analysis software, and report output software in the relevant system test environment are a new rule engine developed based on Drools (an open source rule engine). The software design system test environment is as follows: (1) Database server: CPU 2.5Hz × 8 cores × 2, memory 24GB, disk 500GB; (2) Application server: CPU 2.0Hz × 4 cores × 4, memory 4GB, disk 500GB; (3) Operating system: Windows Server 2008. The development languages used are Java, C#, and Python.

[0103] like Figure 9 As shown, in this embodiment, a rule engine based on APIs (Application Programming Interfaces) is adopted. The rule engine APIs mainly cooperate with the medical diagnosis and treatment rule base. When using the rule engine APIs to establish the medical diagnosis and treatment rule base, the main considerations are the rule authentication environment, rule editor and debugging tools, and user interface of the medical diagnosis and treatment rules. On the other hand, for the rule engine APIs themselves, the main considerations are the rule engine core, engine interface, rule management, execution unit, agenda, and working memory. In addition, the rule engine APIs can also be connected with other extension components and external applications and interact based on medical diagnosis and treatment rules.

[0104] The primary development language for the integrated Chinese and Western medicine clinical decision support system is Java, and the overall architecture is a browser / server (B / S) model. All functions and services are implemented on the web. The front-end framework for the system's functions is EasyUI (a collection of UI plug-ins), which is responsible for the overall presentation of the system client. The interactive interface between the clinical business system and the integrated Chinese and Western medicine clinical decision support system was developed using C#. IntelliJ IDEA (an integrated development environment) was used as the development tool, with load balancing provided by the middleware Tomcat (a web application server) and Nginx (an HTTP and reverse proxy web server).

[0105] In this embodiment, the user interface uses the front-end development technologies HTML (Hypertext Markup Language) and Java Script (a programming language used for website development). The database management system will use SQL Server database and Redis database; the decision analysis software uses data analysis software and machine learning model libraries, including data analysis software such as Python's data analysis library, such as NumPy (Numerical Python, an open source scientific computing library based on Python), Pandas (a data analysis module based on Python), Scikit-learn (a software machine learning library based on Python), TensorFlow (a symbolic mathematics system based on data flow programming), etc.; the report output module uses report generation tools such as JasperReports. The knowledge base management software uses knowledge graph technology combined with advanced Protégé (open source code software).

[0106] The open clinical decision support system for integrating traditional Chinese and Western medicine proposed in this embodiment is essentially an open clinical decision support system for integrating traditional Chinese and Western medicine with a new rule engine. By constructing a database of real medical information, a clinical guideline knowledge base, a clinical decision-making and treatment system, a clinical medical information platform, a platform for clinical data and experience from classic Chinese medicine cases and modern and famous traditional Chinese medicine practitioners, etc., this clinical decision support system for integrating traditional Chinese and Western medicine conforms to the thinking of Evidence-Based Medicine (EBM). Through the deep integration of artificial intelligence in the medical field, a software and hardware system is constructed that can automatically integrate traditional Chinese and Western medical record data, auxiliary diagnosis, personalized treatment, prognosis assessment, and knowledge graph construction, while also taking into account real-time updates and privacy protection. The system supports intelligent diagnostic real-time monitoring instruments, and realizes real-time data collection, integration and analysis, knowledge graphs, auxiliary algorithms, cross-validation, model matching, security mechanisms, continuous knowledge updates, etc. It also supports Chinese and English bilingual search engines and language systems, and involves an intuitive and easy-to-use user interface. It supports the interaction between clinicians and the system, complies with the latest medical knowledge base, medical system semantics and related traditional Chinese medicine corpus, and supports the formulation of joint diagnosis and treatment plans of Chinese and Western medicine.

[0107] The technical challenges of the integrated Chinese and Western medicine clinical decision support system in this embodiment are: (1) Data integration and processing: Effectively integrating and processing multi-source data such as Chinese and Western medicine clinical data, medical records, and medical knowledge bases to ensure data accuracy and consistency. (2) Developing intelligent algorithms suitable for integrated Chinese and Western medicine treatment that can process complex medical data and generate personalized diagnosis and treatment plans. (3) Ensuring that all parts of the software and hardware systems can be seamlessly integrated and operate stably, while ensuring the system's compatibility with existing medical equipment.

[0108] The technical advantages of the integrated Chinese and Western medicine clinical decision support system in this embodiment are: (1) Innovation: The integrated Chinese and Western medicine clinical decision support system adopts cutting-edge integrated Chinese and Western medicine theories and methods, combines the latest medical technology and data analysis and processing technology, and effectively integrates multi-source data. (2) Uniqueness: The integrated Chinese and Western medicine clinical decision support system has a unique algorithm, namely a decision support algorithm based on machine learning and artificial intelligence, which can meet the computing needs of the integrated Chinese and Western medicine clinical decision support system. Through machine learning and artificial intelligence technology, it is different from the existing clinical decision support system and has unique advantages and application value in the field of integrated Chinese and Western medicine. (3) Efficiency: The integrated Chinese and Western medicine clinical decision support system provides faster, more accurate and personalized clinical decision support, helping clinicians to better formulate diagnosis and treatment plans and improve medical efficiency and efficacy. (4) Under the knowledge base-based CDSS rules, the integrated Chinese and Western medicine clinical decision support system modularizes the relevant environment, combines personalized medicine, genomics, bioinformatics, etc. to achieve precision medicine and personalized treatment, and provides more accurate diagnosis and treatment recommendations. (5) Scalability: The integrated Chinese and Western medicine clinical decision support system has good scalability and flexibility, supporting applications in different medical scenarios and clinical needs, and providing possibilities for future technology upgrades and expansion. (6) Practicality: Fully considering the actual clinical needs, working closely with medical institutions and clinicians to achieve an effective combination of technology and clinical practice, bringing practical applications and changes to the medical industry. (7) Security: Using advanced data encryption and privacy protection technologies to ensure the security and privacy of medical data, in compliance with relevant regulations and standards.

[0109] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0110] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0111] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A clinical decision support system integrating traditional Chinese and Western medicine, characterized in that: The clinical decision support system for integrated Chinese and Western medicine includes a user interface module, a data management module, a knowledge base module, a rule engine module, and a decision analysis module; the user interface module is connected to the data management module, the knowledge base module, the rule engine module, and the decision analysis module respectively; the rule engine module is also connected to the data management module and the knowledge base module respectively; and the decision analysis module is also connected to the data management module, the knowledge base module, and the rule engine module respectively; The user interface module is used to obtain patient information input by a clinician and transmit the patient information to the data management module, wherein the patient information includes patient personal information, disease symptoms and examination results; The data management module is used to store the patient information, perform data cleaning and mapping of Chinese and Western medical terms on the patient information to obtain processed patient information, and transmit the processed patient information to the rule engine module; The mapping process of Chinese and Western medical terms is used to make the Chinese and Western medical terms consistent; The knowledge base module is used to store medical knowledge and diagnosis and treatment guidelines, track and update the medical knowledge and diagnosis and treatment guidelines in real time, and transmit the latest medical knowledge and diagnosis and treatment guidelines to the rule engine module; The medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavior guidelines related to medical diagnosis and treatment of traditional Chinese medicine and Western medicine; The rule engine module is used to establish a medical diagnosis and treatment rule library based on the medical knowledge and diagnosis and treatment guidelines, and retrieve corresponding medical diagnosis and treatment rules from the medical diagnosis and treatment rule library based on the processed patient information, generate preliminary diagnosis results and treatment plans based on the medical diagnosis and treatment rules, and transmit the preliminary diagnosis results and treatment plans to the decision analysis module; the medical diagnosis and treatment rule library includes a plurality of medical diagnosis and treatment rules, each of which includes the name of a disease, disease symptoms and corresponding diagnosis results and treatment plans; The decision analysis module is used to perform decision analysis and optimization on the preliminary diagnosis results and treatment plans to obtain the final diagnosis results and treatment plans.

2. The clinical decision support system for integrating traditional Chinese and Western medicine according to claim 1, characterized in that: The user interface module includes a user input unit, a human-computer interaction unit and a user interface display unit; The user input unit is used to receive the patient information input by the clinician and transmit the patient information to the data management module; The human-computer interaction unit is used for human-computer interaction between the clinician and the system; The user interface display unit is used to visually display the final diagnosis result and treatment plan.

3. The clinical decision support system combining traditional Chinese and western medicine according to claim 1, characterized in that: The data management module includes a data storage unit and a data cleaning and preprocessing unit; The data storage unit is used to store the patient information; The data cleaning and preprocessing unit is used to clean the patient information, establish a virtual case based on the patient information after data cleaning, and perform Chinese and Western medicine medical terminology mapping processing based on the patient information after data cleaning and the virtual case to obtain the processed patient information, and transmit the processed patient information to the rule engine module.

4. The clinical decision support system combining traditional Chinese and Western medicine according to claim 1, characterized in that: The knowledge base module includes a knowledge entry unit and a knowledge update unit; The knowledge input unit is used to input and store the medical knowledge and diagnosis and treatment guidelines; The knowledge updating unit is used to track and update the medical knowledge and diagnosis and treatment guidelines in real time, and transmit the latest medical knowledge and diagnosis and treatment guidelines to the rule engine module.

5. The clinical decision support system combining traditional Chinese and western medicine according to claim 1, characterized in that: The rule engine module includes a rule base management unit and a rule base execution engine unit; The rule base management unit is used to establish a medical diagnosis and treatment rule base based on the medical knowledge and diagnosis and treatment guidelines, and to perform management operations on the medical diagnosis and treatment rules in the medical diagnosis and treatment rule base, wherein the management operations include adding medical diagnosis and treatment rules, modifying medical diagnosis and treatment rules, and deleting medical diagnosis and treatment rules; The rule base execution engine unit is used to dynamically load diagnosis and treatment rules and matching decision models, and according to the processed patient information, use the diagnosis and treatment rules and matching decision models to parse the processed patient information and all medical diagnosis and treatment rules, and retrieve the medical diagnosis and treatment rules corresponding to the processed patient information from the medical diagnosis and treatment rule base, generate preliminary diagnosis results and treatment plans according to the medical diagnosis and treatment rules, and transmit the preliminary diagnosis results and treatment plans to the decision analysis module; The diagnosis and treatment rules and matching decision model is a model established based on disease symptoms and medical diagnosis and treatment rules, and is used to match corresponding medical diagnosis and treatment rules according to disease symptoms in patient information.

6. The clinical decision support system combining traditional Chinese and western medicine according to claim 1, characterized in that: The decision analysis module includes a machine learning unit and a decision analysis unit; The machine learning unit is used to analyze and learn historical data using machine learning technology to improve the decision-making performance of the decision analysis unit; the historical data includes historical patient information and corresponding historical diagnosis results and historical treatment plans; The decision analysis unit is used to perform comprehensive comparison and decision analysis based on the preliminary diagnosis results and treatment plans and the historical data to obtain the final diagnosis results and treatment plans.

7. The clinical decision support system for integrating traditional Chinese and Western medicine according to claim 1, characterized in that: The clinical decision support system for integrated Chinese and Western medicine further comprises a report output module, which is connected to the decision analysis module and the user interface module respectively, and comprises a report analysis unit and a report display unit; The report analysis unit is used to generate a diagnosis and treatment report based on the final diagnosis result and treatment plan; The report display unit is used to transmit the diagnosis and treatment report to the user interface module for visual display.

8. The clinical decision support system combining traditional Chinese and western medicine according to claim 7, characterized in that: The report analysis unit adopts JasperReports or Crystal Reports report generation tool.

9. The clinical decision support system for integrating traditional Chinese and Western medicine according to claim 1, characterized in that: The clinical decision support system integrating traditional Chinese and Western medicine is provided with a mediator pattern, which constructs a mediator chain of many-to-many components in the form of multiple mediators. The mediator chain is used to coordinate the communication between the user interface module, the data management module, the knowledge base module, the rule engine module and the decision analysis module.

10. A clinical decision support method combining traditional Chinese and Western medicine, characterized in that: The clinical decision support method of integrating traditional Chinese and Western medicine includes: Obtaining patient information, including patient personal information, disease symptoms, and examination results; Performing data cleaning and mapping of Chinese and Western medical terms on the patient information to obtain processed patient information; the mapping of Chinese and Western medical terms is used to ensure consistency between Chinese and Western medical terms; Based on the processed patient information, the corresponding medical diagnosis and treatment rules are retrieved from a medical diagnosis and treatment rule library, and a preliminary diagnosis result and treatment plan are generated based on the medical diagnosis and treatment rules; the medical diagnosis and treatment rule library is a database including a plurality of medical diagnosis and treatment rules established based on medical knowledge and diagnosis and treatment guidelines, wherein the medical knowledge and diagnosis and treatment guidelines are pre-entered basic knowledge and behavior guidelines related to medical diagnosis and treatment of traditional Chinese medicine and Western medicine, and each medical diagnosis and treatment rule includes the name of a disease, disease symptoms, and corresponding diagnosis results and treatment plan; Perform decision analysis and optimization on the preliminary diagnosis results and treatment plans to obtain final diagnosis results and treatment plans.

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