Traditional Chinese medicine AI diagnosis and treatment training integrated system based on large model

Abstract

The invention relates to the technical field of medical systems, and discloses a traditional Chinese medicine AI diagnosis and treatment training integrated system based on a large model, and the system comprises a symptom input module which is used for comprehensively collecting patient information; the doctor end module is connected with the symptom input module and is used for receiving the inquiry sheet, auditing and operating an AI large model for intelligent inquiry and finally generating a prescription order; the AI large model module is connected with the doctor end module and used for integrating traditional Chinese medicine ancient books and case data and conducting intelligent diagnosis and prescription recommendation; and the traditional Chinese medicine supervision and toxicity detection module is connected with the AI large model module and is used for performing pharmacology and toxicity detection on the prescription output by the AI large model module to ensure the medication safety.

Description

Technical Field

[0001] The present invention relates to the field of medical systems, and in particular to a large-model-based integrated system for TCM AI diagnosis and treatment training. Background Art

[0002] Since the concept of artificial intelligence (AI) was first proposed at the Dartmouth Symposium in the United States in 1956, AI technology has developed rapidly in various fields, especially in the medical field. Early medical expert systems, such as the MYCIN system born at Stanford University in the United States in 1976, pioneered the application of AI in the medical field. Subsequently, traditional Chinese medicine, as a treasure of Chinese civilization, also began to explore the combination with AI technology.

[0003] In 1978, the first TCM AI expert system, "Guan Youbo's liver disease diagnosis and treatment program", was born at the Beijing University of Traditional Chinese Medicine, which was a milestone in the history of TCM. The system was developed by Professor Guan Youbo, a famous TCM expert, based on his experience in treating liver diseases and combined with computer technology, marking the birth of TCM AI expert systems. Since then, TCM AI expert systems have developed rapidly in China, and a wide variety of systems have emerged, providing an important means for inheriting and promoting the experience of famous TCM doctors in syndrome differentiation and treatment.

[0004] However, despite the achievements of TCM AI expert systems, there are still many deficiencies in their popularization and application. Traditional TCM AI systems mostly rely on the input of symptom parameters based on the four diagnostic methods of "looking, smelling, asking, and touching", which limits their scope of use and popularity. In addition, the distribution of TCM resources is seriously unbalanced. Excellent TCM hospitals, TCM practitioners, and TCM resources are mainly concentrated in large cities with relatively developed economies, while small cities, towns, rural areas, and remote areas face the dilemma of "lack of doctors and medicines". The diagnosis and treatment level of TCM practitioners at the grassroots level is generally low, and due to limited conditions, it is difficult to carry out large-scale and wide-coverage education and training of TCM, which affects the physical health of the general public and the social development of remote areas.

[0005] To solve the above problems, this application proposes an integrated system of TCM AI diagnosis and treatment training based on a large model. Summary of the invention

[0006] 1. Purpose of the invention In order to solve the technical problems existing in the background technology, the present invention proposes an integrated system of TCM AI diagnosis and treatment training based on a large model, which is conducive to the promotion of remote assisted learning.

[0007] (II) Technical solution To solve the above problems, the present invention provides an integrated system for TCM AI diagnosis and treatment training based on a large model, comprising: Symptom input module, used to comprehensively collect patient information; The doctor-side module is connected to the disease input module to receive the medical consultation form, review and operate the AI ​​big model for intelligent consultation, and finally generate a prescription order; The AI ​​big model module is connected to the doctor-side module to integrate ancient Chinese medical books and case data for intelligent diagnosis and prescription recommendations; The TCM pharmacology supervision and toxicity detection module is connected to the AI ​​big model module to perform pharmacology and toxicity detection on the prescriptions output by the AI ​​big model module to ensure the safety of medication; The display and self-learning module is connected with the TCM pharmacology supervision and toxicity detection module to display the diagnosis results, provide learning materials, and help TCM enthusiasts and grassroots TCM physicians improve their diagnostic skills; The smart Chinese medicine pharmacy module, as well as the display and self-learning modules, are used to realize the online automatic preparation and delivery of prescription Chinese medicines and build a closed loop of pharmaceutical services.

[0008] Preferably, the disease input module includes: The patient information entry submodule is used to enter the patient information: including but not limited to name, gender, date of birth, age, ethnicity, marital status, family medical history, personal allergy history, telephone number, and email address; The natural language sentence input submodule includes two parts: natural sentence input and natural speech input; In the natural language input part, doctors or patients only need to type natural language sentences on the computer keyboard to describe and ask questions about the patient's condition; In the natural speech input part, patients can use the microphone to describe their symptoms and ask questions to the TCM AI model in natural speech. The disease symptom field text check input submodule is used to check and input according to the disease symptom field. First, select the department to be consulted, such as internal medicine or gynecology, then select the disease, such as cold, high blood pressure, etc. Finally, check the corresponding disease symptoms, such as sneezing, dry throat, and cough, on the computer display page; Individual TCM index input submodule, this submodule mainly focuses on the input of information in the process of TCM four examinations and combined syndrome differentiation and treatment, such as human pulse information, tongue coating information, and physical constitution information.

[0009] The human biochemical index input submodule mainly focuses on the input of human medical biochemical indexes and other Western medicine auxiliary diagnosis and treatment information, including but not limited to body temperature, blood oxygen, blood pressure, blood sugar, and heart rate.

[0010] Preferably, the doctor-side module includes: The medical questionnaire information receiving unit is used to receive medical questionnaire information from the symptom input module, which includes the patient's basic personal information, symptom description, disease symptom check items, Chinese medicine indicators such as pulse and tongue coating, and Western medicine auxiliary diagnosis and treatment information such as body temperature and blood pressure.

[0011] Intelligent consultation operation unit: Doctors use this unit to operate the AI ​​big model module and send the consultation information to the AI ​​big model for intelligent consultation. The AI ​​big model will perform reasoning and analysis based on this information, combined with ancient Chinese medical books, secret prescriptions, and massive medical record prescription data, to generate preliminary consultation results. Medical consultation result review unit: Doctors need to carefully review the consultation results generated by the AI ​​model and make necessary modifications and adjustments to the AI's preliminary conclusions based on their own professional knowledge and experience to ensure the accuracy and rationality of the diagnosis; Signature confirmation unit: After confirming that the consultation results are correct, the doctor needs to sign and confirm the final consultation results through the signature confirmation unit. This step is a key link to ensure the legality and validity of the consultation results.

[0012] Prescription generation and sending unit: The consultation result signed and confirmed by the doctor will be converted into a prescription order, and the unit will be responsible for sending the prescription order to the smart Chinese medicine pharmacy module for subsequent Chinese medicine decoction and delivery services; Medical consultation record management unit: Responsible for storing and managing each consultation record, including the original consultation form, the preliminary results of the AI ​​big model, the doctor's review and modification records and the final signature confirmation results, providing data support for subsequent medical record analysis, academic research and system optimization.

[0013] Preferably, the TCM pharmacology supervision and toxicity detection module includes: The pharmacology supervision sub-unit is used to review the rationality of the drug compatibility, efficacy and indications in the prescription according to the pharmacology matching mechanism in the classic books of traditional Chinese medicine and the relevant national regulations or standards for the use of traditional Chinese medicine, to ensure that the prescription conforms to the conventional theory and practice of traditional Chinese medicine; The toxicity detection subunit is used to detect the toxicity of the dosage of a single drug or a combination of drugs in a prescription, and strictly examine the dosage and potential toxicity of the drug according to the national "Pharmacopoeia" and other relevant standards. For prescriptions that do not meet the toxicity safety standards, timely warnings are given to ensure the safety of patients' medication; The data comparison subunit is used in the process of pharmacological supervision and toxicity testing. It may be necessary to compare the application of different prescriptions and drugs in different diseases and the feedback on their efficacy. This subunit provides data support to facilitate rapid comparison and analysis to improve the accuracy and reliability of decision-making.

[0014] Prescription review report generation subunit: After completing pharmacology supervision and toxicity testing, this subunit is responsible for generating a detailed prescription review report. The report should include prescription analysis, drug combination rationality, and toxicity assessment for reference by professional doctors, who will ultimately decide whether to accept or modify the prescription; To improve the efficiency of prescription review, the automatic prescription review sub-unit conducts preliminary review of prescriptions output by the AI ​​large model based on preset algorithms and rules. It immediately excludes or issues warnings for prescriptions that are obviously unreasonable or potentially dangerous, thereby reducing the burden of manual review.

[0015] Preferably, the demonstration and self-study modules include: The TCM syndrome differentiation diagnosis conclusion submodule gives the TCM AI big model’s syndrome differentiation diagnosis conclusion based on the patient’s symptoms and questions input; The submodule for displaying the treatment principles of syndrome differentiation and treatment provides relevant treatment principles of syndrome differentiation and treatment for the input patient symptoms and questions, for reference by TCM physicians and TCM enthusiasts; The TCM prescription and book source submodule gives the name of the TCM prescription and the book source according to the patient's symptoms and questions, so that TCM practitioners and TCM enthusiasts can understand and clarify the source of the prescription and the reason for prescribing it. Reference prescription and diet therapy submodule, which provides specific TCM prescriptions for TCM physicians to decide and sign.

[0016] Preferably, the prescription receiving and reviewing subunit includes: Receive prescription orders from TCM pharmacology supervision and verified by toxicity detection module.

[0017] Prescriptions are reviewed by Chinese medicine pharmacists to ensure their legality and safety.

[0018] The medicine dispensing and preparation sub-unit is responsible for accurately dispensing and preparing medicines in the Chinese medicine pharmacy according to the approved prescriptions; The decoction and packaging subunit is used to decoct the prepared Chinese medicine to ensure that the decoction time and temperature meet the Chinese medicine decoction specifications; After decoction, the Chinese medicine is packaged so that it can be delivered to patients safely and conveniently.

[0019] The distribution and logistics sub-unit is used to deliver the decocted and packaged Chinese medicine to the patient's designated address in a timely manner.

[0020] Provide logistics information tracking services so that patients can understand the delivery status of traditional Chinese medicine at any time.

[0021] The status feedback subunit is used to update the prescription status information in real time during the delivery process and send it to the doctor-side module so that the doctor can understand the delivery progress of the traditional Chinese medicine; After delivery is completed, a notification message will be pushed to the patient to inform him or her that he or she has received the Chinese medicine and to remind him or her to take it as prescribed by the doctor.

[0022] The above technical solution of the present invention has the following beneficial technical effects: 1. Improve the popularity and convenience of TCM diagnosis and treatment Remote diagnosis and treatment: Through natural language and disease symptom field check input, patients can enjoy TCM diagnosis and treatment services without having to visit the site in person, effectively solving the problem of uneven distribution of medical resources and enabling remote areas and grassroots people to obtain high-quality TCM diagnosis and treatment.

[0023] Mobile Internet: Deep integration with modern mobile Internet, Internet of Things, and 5G new technologies realizes remote and instant Chinese medicine diagnosis and treatment, improving the convenience of diagnosis and treatment.

[0024] 2. Improve the accuracy and efficiency of TCM diagnosis and treatment Big data support: The TCM AI big model integrates a large amount of ancient Chinese medical books and medical record prescription data. Through big data analysis and artificial intelligence algorithms, it can provide more accurate diagnosis results and treatment plans.

[0025] Personalized diagnosis and treatment: Based on the patient's specific condition and symptoms, the AI ​​big model can prescribe personalized dialectical diagnosis, treatment principles and prescriptions for each person, improving the pertinence and effectiveness of diagnosis and treatment.

[0026] 3. Promote TCM education and training Remote training: It provides a remote assisted learning and training platform for grassroots TCM practitioners, students of Chinese / Western medical schools, and TCM enthusiasts, making the inheritance of TCM diagnosis and treatment experience and knowledge more extensive and in-depth.

[0027] Self-directed learning: The display and self-directed learning modules provide structured learning materials to help learners quickly grasp the key points of disease diagnosis and treatment principles, and improve their TCM diagnosis and treatment level.

[0028] 4. Ensure medication safety and efficacy Pharmacological supervision and toxicity testing: The TCM pharmacological supervision and toxicity testing module conducts pharmacological supervision and toxicity testing on the prescriptions output by the AI ​​large model to ensure the safety and efficacy of medication and reduce the risks caused by improper medication.

[0029] 5. Achieve a closed loop of pharmaceutical services Smart Pharmacy: The smart Chinese medicine pharmacy module completes the online automatic preparation of prescription Chinese medicines and timely home delivery, forming a closed loop of pharmaceutical services for remote Chinese medicine-assisted diagnosis and treatment, improving the integrity of diagnosis and treatment services and patient satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a structural schematic diagram of a large-model-based integrated system for TCM AI diagnosis and treatment training proposed in the present invention.

[0031] Figure 2 This is a structural schematic diagram of the disease input module in the integrated system of TCM AI diagnosis and treatment training based on a large model proposed by the present invention.

[0032] Figure 3 This is a structural schematic diagram of the doctor-side module in the integrated system of TCM AI diagnosis and treatment training based on a large model proposed by the present invention.

[0033] Figure 4 This is a structural schematic diagram of the TCM pharmacology supervision and toxicity detection module in the TCM AI diagnosis and treatment training integrated system based on a large model proposed by the present invention.

[0034] Figure 5 This is a structural schematic diagram of the display and autonomous learning modules in the integrated system of TCM AI diagnosis and treatment training based on a large model proposed by the present invention.

[0035] Figure 6 This is a structural schematic diagram of the prescription receiving and reviewing subunit in the integrated system of TCM AI diagnosis and treatment training based on a large model proposed by the present invention.

[0036] Figure numerals: 101, symptom input module; 1011, patient information input submodule; 1012, natural language sentence input submodule; 1013, disease symptom field text check input submodule; 1014, individual Chinese medicine index input submodule; 1015, human biochemical index input submodule; 102, doctor end module; 1021, consultation form information receiving unit; 1022, intelligent consultation operation unit; 1023, consultation result review unit; 1024, signature confirmation unit; 1025, prescription generation and sending unit; 1026, consultation Record management unit; 103. AI big model module; 104. TCM pharmacology supervision and toxicity detection module; 105. Display and self-learning module; 1051. TCM syndrome differentiation diagnosis conclusion sub-module; 1052. Syndrome differentiation and treatment principle display sub-module; 1053. TCM prescriptions and classic sources sub-module; 1054. Reference prescriptions and diet therapy sub-module; 106. Smart Chinese medicine pharmacy module; 1061. Medicine picking and preparation sub-unit; 1062. Decoction and packaging sub-unit; 1063. Distribution and logistics sub-unit; 1064. Status feedback sub-unit. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0038] like Figure 1-6 As shown, the present invention proposes a large-model-based integrated system for TCM AI diagnosis and treatment training, including: Symptom input module 101, used to comprehensively collect patient information; Specifically, the symptom input module includes: Patient information input submodule 1011 is used to input patient information: including but not limited to name, gender, date of birth, age, ethnicity, marital status, family medical history, personal allergy history, telephone number, and email address; The natural language sentence input submodule 1012 includes two parts: natural sentence input and natural speech input; In the natural language input part, doctors or patients only need to type natural language sentences on the computer keyboard to describe and ask questions about the patient's condition; In the natural speech input part, patients can use the microphone to describe their symptoms and ask questions to the TCM AI model in natural speech. Disease symptom field text selection input submodule 1013, this submodule selects and inputs according to the disease symptom field, first selects the department to be consulted such as internal medicine, gynecology, then selects the disease such as cold, hypertension, and finally selects the corresponding disease symptoms such as sneezing, dry throat, and cough on the computer display page; Individual TCM index input submodule 1014, this submodule mainly focuses on the input of information in the process of TCM four-diagnosis combined syndrome differentiation and treatment, such as human pulse information, tongue coating information, and physical constitution information.

[0039] The human biochemical index input submodule 1015 mainly focuses on the input of human medical biochemical index Western medicine auxiliary diagnosis and treatment information, including but not limited to body temperature, blood oxygen, blood pressure, blood sugar, and heart rate.

[0040] The doctor-side module 102 is connected to the symptom input module 101 and is used to receive the medical consultation form, review and operate the AI ​​big model for intelligent medical consultation, and finally generate a prescription order; The doctor-side module 102 includes: The medical questionnaire information receiving unit 1021 is used to receive the medical questionnaire information from the symptom input module 101, which includes the patient's basic personal information, symptom description, disease symptom check boxes, Chinese medicine indicators such as pulse, tongue coating, and Western medicine auxiliary diagnosis and treatment information such as body temperature and blood pressure.

[0041] Intelligent consultation operation unit 1022: The doctor operates the AI ​​big model module 103 through this unit and sends the consultation form information to the AI ​​big model for intelligent consultation. The AI ​​big model will perform reasoning analysis based on this information, combined with ancient Chinese medical books, secret prescriptions, and massive medical record prescription data, to generate preliminary consultation results; Medical consultation result review unit 1023: Doctors need to carefully review the consultation results generated by the AI ​​model and make necessary modifications and adjustments to the AI's preliminary conclusions based on their own professional knowledge and experience to ensure the accuracy and rationality of the diagnosis; Signature confirmation unit 1024: After confirming that the consultation results are correct, the doctor needs to sign and confirm the final consultation results through the signature confirmation unit. This step is a key link to ensure the legality and validity of the consultation results.

[0042] Prescription generation and sending unit 1025: The consultation result signed and confirmed by the doctor will be converted into a prescription order, and the unit will be responsible for sending the prescription order to the smart Chinese medicine pharmacy module 106 for subsequent Chinese medicine decoction and delivery services; Medical consultation record management unit 1026: Responsible for storing and managing each consultation record, including the original consultation form, the preliminary results of the AI ​​big model, the doctor's review and modification records and the final signature confirmation results, providing data support for subsequent medical record analysis, academic research and system optimization.

[0043] The AI ​​big model module 103 is connected to the doctor-side module 102 and is used to integrate ancient Chinese medical books and case data to perform intelligent diagnosis and prescription recommendations; The Chinese medicine pharmacology supervision and toxicity detection module 104 is connected to the AI ​​big model module 103 and is used to perform pharmacology and toxicity detection on the prescription output by the AI ​​big model module 103 to ensure the safety of medication; The display and self-learning module 105 is connected to the TCM pharmacology supervision and toxicity detection module 104, and is used to display the diagnosis results, provide learning materials, and help TCM enthusiasts and grassroots TCM physicians improve their diagnosis level; The smart Chinese medicine pharmacy module 106 and the display and self-learning module 105 are used to realize the online automatic preparation and distribution of prescription Chinese medicines and build a closed loop of pharmaceutical services.

[0044] Preferably, the Chinese medicine pharmacology supervision and toxicity detection module 104 includes: Pharmacology supervision subunit 1041 is used to review the rationality of drug compatibility, efficacy and indications in prescriptions based on the pharmacological matching mechanism in TCM classics and relevant national TCM use norms or standards to ensure that the prescriptions are in line with TCM theory and practice; The toxicity detection subunit 1042 is used to detect the toxicity of the dosage of a single drug or a combination of drugs in a prescription, and to strictly review the dosage and potential toxicity of the drug according to the national pharmacopoeia and other relevant standards. For prescriptions that do not meet the toxicity safety standards, timely warnings are given to ensure the safety of patients' medication; The data comparison subunit 1043 is used in the process of pharmacological supervision and toxicity testing. It may be necessary to compare the application of different prescriptions and drugs in different diseases and the feedback on the efficacy. This subunit provides data support to facilitate rapid comparison and analysis to improve the accuracy and reliability of decision-making.

[0045] Prescription review report generation subunit 1044: After completing pharmacology supervision and toxicity testing, this subunit is responsible for generating a detailed prescription review report, which should include prescription analysis, drug combination rationality, and toxicity assessment content for reference by professional doctors, who will ultimately decide whether to accept or modify the prescription; The automatic prescription review subunit 1045 conducts a preliminary review of the prescriptions output by the AI ​​large model based on preset algorithms and rules to improve the efficiency of prescription review. It immediately excludes or issues warnings for prescriptions that are obviously unreasonable or potentially dangerous, thereby reducing the burden of manual review.

[0046] Specifically, the display and self-learning module 105 includes: TCM syndrome differentiation diagnosis conclusion submodule 1051, based on the input patient symptoms and questions, this submodule gives the TCM AI big model’s syndrome differentiation diagnosis conclusion; The submodule 1052 for displaying treatment principles based on syndrome differentiation is used to provide relevant treatment principles based on syndrome differentiation according to the input patient symptoms and questions for reference by TCM physicians and TCM enthusiasts. The TCM prescription and book source submodule 1053 provides the name of the TCM prescription and the book source according to the patient's symptoms and questions input, so that TCM doctors and TCM enthusiasts can understand and clarify the source of the prescription and the reason for prescribing the prescription; Reference prescription and diet therapy submodule 1054, which provides specific Chinese medicine prescriptions for Chinese medicine practitioners to decide and sign.

[0047] Specifically, the prescription receiving and reviewing subunit 106 includes: Receive prescription orders verified by the traditional Chinese medicine pharmacology supervision and toxicity detection module 104.

[0048] Prescriptions are reviewed by Chinese medicine pharmacists to ensure their legality and safety.

[0049] The medicine dispensing and preparation subunit 1061 performs accurate medicine dispensing and preparation work in the Chinese medicine pharmacy according to the approved prescription; The decoction and packaging subunit 1062 is used to decoct the prepared Chinese medicine to ensure that the decoction time and temperature meet the Chinese medicine decoction specifications; After decoction, the Chinese medicine is packaged so that it can be delivered to patients safely and conveniently.

[0050] The distribution and logistics subunit 1063 is used to deliver the decocted and packaged Chinese medicine to the address specified by the patient in a timely manner.

[0051] Provide logistics information tracking services so that patients can understand the delivery status of traditional Chinese medicine at any time.

[0052] The status feedback subunit 1064 is used to update the prescription status information in real time during the distribution process and send it to the doctor-side module 102 so that the doctor can understand the distribution progress of the traditional Chinese medicine; After delivery is completed, a notification message will be pushed to the patient to inform him or her that he or she has received the Chinese medicine and to remind him or her to take it as prescribed by the doctor.

[0053] It should be understood that the above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation of the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. In addition, the appended claims of the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalent forms of such scope and boundaries.

Claims

1. A large-model-based integrated system for TCM AI diagnosis and treatment training, characterized in that: include: A disease condition input module (101) is used to comprehensively collect patient information; The doctor-side module (102) is connected to the symptom input module (101) and is used to receive the medical consultation form, review and operate the AI ​​big model to conduct intelligent medical consultation, and finally generate a prescription order; The AI ​​big model module (103) is connected to the doctor-side module (102) and is used to integrate ancient Chinese medical books and case data to perform intelligent diagnosis and prescription recommendations; The Chinese medicine pharmacology supervision and toxicity detection module (104) is connected to the AI ​​large model module (103) and is used to perform pharmacology and toxicity detection on the prescription output by the AI ​​large model module (103). The display and self-learning module (105) is connected with the TCM pharmacology supervision and toxicity detection module (104) to display the diagnosis results and provide learning materials; The smart Chinese medicine pharmacy module (106) and the display and self-learning module (105) are used to realize the online automatic preparation and distribution of prescription Chinese medicines and build a closed loop of pharmaceutical services.

2. According to the large model-based integrated system for TCM AI diagnosis and treatment training according to claim 1, it is characterized in that: The disease input module includes: The patient information input submodule (1011) is used to input the patient information: including name, gender, date of birth, age, ethnicity, marital status, family medical history, personal allergy history, telephone number, and email address; The natural language sentence input submodule (1012) includes two parts: natural sentence input and natural speech input; In the natural language input part, doctors or patients only need to type natural language sentences on the computer keyboard to describe and ask questions about the patient's condition; In the natural speech input part, patients can use the microphone to describe their symptoms and ask questions to the TCM AI model in natural speech. Disease symptom field text check input submodule (1013), this submodule checks and inputs according to the disease symptom field, first selects the consultation department, then selects the disease, and finally checks the corresponding disease symptoms on the computer display page; Individual TCM index input submodule (1014), which mainly focuses on the input of information in the process of TCM four-diagnosis combined with syndrome differentiation and treatment; The human biochemical index input submodule (1015) mainly focuses on the input of human medical biochemical index Western medicine auxiliary diagnosis and treatment information.

3. According to claim 2, a large model-based integrated system for TCM AI diagnosis and treatment training is characterized in that: The doctor-side module (102) includes: A medical questionnaire information receiving unit (1021), used for receiving medical questionnaire information from the symptom input module (101); Intelligent consultation operation unit (1022): The doctor uses this unit to operate the AI ​​big model module (103) and sends the consultation form information to the AI ​​big model for intelligent consultation. The AI ​​big model will perform reasoning analysis based on this information and generate preliminary consultation results. Medical consultation result review unit (1023): Doctors need to carefully review the consultation results generated by the AI ​​model and make necessary modifications and adjustments to the AI's preliminary conclusions based on their own professional knowledge and experience; Signature confirmation unit (1024): After confirming that the consultation result is correct, the doctor needs to sign and confirm the final consultation result through the signature confirmation unit; Prescription generation and sending unit (1025): The consultation result signed and confirmed by the doctor will be converted into a prescription order, and the unit will be responsible for sending the prescription order to the smart Chinese medicine pharmacy module (106); Medical consultation record management unit (1026): Responsible for storing and managing each consultation record, including the original consultation form, the preliminary results of the AI ​​big model, the doctor's review and modification records, and the final signature confirmation results.

4. According to claim 3, a large model-based integrated system for TCM AI diagnosis and treatment training is characterized in that: The Chinese Medicine Pharmacology Supervision and Toxicity Testing Module (104) includes: The Pharmacology Supervision Sub-unit (1041) is used to review the rationality of the drug compatibility, efficacy and indications in the prescription according to the pharmacological matching mechanism in the classics of traditional Chinese medicine and the relevant national regulations or standards for the use of traditional Chinese medicine; Toxicity detection subunit (1042), used to detect the toxicity of a single drug or a compound drug in a prescription, and to give a warning in a timely manner for a prescription that does not meet the toxicity safety standard; Data comparison subunit (1043), used in pharmacology supervision and toxicity testing to improve the accuracy and reliability of decision making; Prescription review report generation subunit (1044), after completing pharmacological supervision and toxicity testing, this subunit is responsible for generating a detailed prescription review report and ultimately deciding whether to accept or modify the prescription; The automatic prescription review subunit (1045) performs a preliminary review of the prescriptions output by the AI ​​large model based on preset algorithms and rules, and excludes or issues warnings for prescriptions that are obviously unreasonable or potentially dangerous.

5. According to claim 4, a large model-based integrated system for TCM AI diagnosis and treatment training is characterized in that: The demonstration and self-study modules (105) include: TCM syndrome differentiation diagnosis conclusion submodule (1051), based on the input patient symptoms and questions, this submodule gives the diagnosis conclusion of the TCM AI big model based on syndrome differentiation and treatment; The submodule (1052) displays the treatment principle of syndrome differentiation and treatment. Based on the input patient symptoms and questions, this submodule provides the relevant treatment principle of syndrome differentiation and treatment for reference by TCM physicians and TCM enthusiasts. The TCM prescription and book source submodule (1053) provides the name of the TCM prescription and the book source according to the patient's symptoms and questions, so that TCM practitioners and TCM enthusiasts can understand and clarify the source of the prescription and the reason for prescribing it; Reference prescription and diet therapy submodule (1054), which provides specific TCM prescriptions for TCM physicians to decide and sign.

6. According to claim 5, a large model-based integrated system for TCM AI diagnosis and treatment training is characterized in that: The prescription receiving and reviewing subunit (106) includes: Receive prescription orders verified by the traditional Chinese medicine pharmacology supervision and toxicity detection module (104); Prescription review by Chinese medicine pharmacists; The medicine dispensing and preparation subunit (1061) performs accurate medicine dispensing and preparation work in the Chinese medicine pharmacy according to the approved prescriptions; The decoction and packaging subunit (1062) is used to decoct the prepared Chinese medicine to ensure that the decoction time and temperature meet the Chinese medicine decoction specifications; The distribution and logistics subunit (1063) is used to deliver the decocted and packaged Chinese medicine to the address specified by the patient in a timely manner; The status feedback subunit (1064) is used to update the prescription status information in real time during the distribution process and send it to the doctor-side module (102) so that the doctor can understand the distribution progress of the traditional Chinese medicine; After delivery is completed, a notification message will be pushed to the patient to inform him or her that he or she has received the Chinese medicine and to remind him or her to take it as prescribed by the doctor.

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