Traditional Chinese medicine auxiliary diagnosis and treatment method, system, device and storage medium

Abstract

The application provides a traditional Chinese medicine auxiliary diagnosis and treatment method, system, device and storage medium, which comprises the following steps: performing keyword analysis on symptom information text describing the symptoms of a patient to obtain symptom words; if the symptom words exist, a prescription associated with the symptom words is obtained; performing correlation degree analysis on medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials associated with the symptoms; and the recommendation degree of the prescription is obtained according to the correlation degree of the associated medicinal materials, so that a target prescription is output according to the recommendation degree. The technical scheme of the application can improve the intelligent degree of the traditional Chinese medicine auxiliary diagnosis and treatment system.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, system, electronic device, and non-transitory computer-readable storage medium for auxiliary diagnosis and treatment in traditional Chinese medicine. Background Technology

[0002] In the information-based TCM service system, we can combine internet technology to establish a basic database focusing on TCM electronic medical records and electronic prescriptions, and a TCM-assisted diagnosis and treatment system to promote integrated online and offline services and telemedicine services.

[0003] Most current TCM auxiliary diagnosis and treatment systems digitize TCM prescriptions and rely on doctors' experience to make judgments and selections, but they cannot perform intelligent symptom diagnosis and prescription recommendations. Summary of the Invention

[0004] This invention provides a method, system, electronic device, and non-transitory computer-readable storage medium for auxiliary diagnosis and treatment in traditional Chinese medicine (TCM), which solves the problem that current TCM auxiliary diagnosis and treatment systems cannot perform intelligent symptom diagnosis and prescription recommendation, thereby improving the intelligence level of TCM auxiliary diagnosis and treatment systems.

[0005] This invention provides a Traditional Chinese Medicine (TCM) auxiliary diagnosis and treatment system, comprising: a parsing module for parsing keywords in symptom information text describing patient symptoms to obtain symptom vocabulary; a symptom diagnosis module for obtaining prescriptions associated with the symptoms corresponding to the symptom vocabulary when the symptom vocabulary exists; a medicinal material analysis module for performing correlation analysis on the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials; and a prescription recommendation module for obtaining the recommendation degree of the prescription based on the correlation degree of the associated medicinal materials, and outputting a target prescription according to the recommendation degree.

[0006] According to a TCM-assisted diagnosis and treatment system provided by the present invention, the system further includes an anomaly detection module, which is used to obtain and output set symptom data from the database when the symptom vocabulary does not exist, so as to display the set symptoms and diagnosis and treatment reference to medical personnel. The set symptom data includes the set symptom name, TCM analysis, Chinese medicine treatment, and reference information.

[0007] According to a TCM auxiliary diagnosis and treatment system provided by the present invention, the symptom diagnosis module is further configured to diagnose one or more prescriptions that can be used to treat the symptoms corresponding to the symptom words based on the symptom words using an intelligent association analysis algorithm. The prescription information is stored in the form of prescription information units, which include prescription name, prescription evaluation module, prescription composition, prescription source, and prescription details.

[0008] According to a TCM auxiliary diagnosis and treatment system provided by the present invention, the medicinal material analysis module is further used to perform correlation analysis on the medicinal material information and the prescription information to obtain the recommendation degree of each prescription, obtain the correlation degree between each medicinal material and the symptoms, and obtain the frequency of medicinal materials corresponding to the symptoms.

[0009] According to a TCM auxiliary diagnosis and treatment system provided by the present invention, the prescription recommendation module includes: a prescription provision submodule, used to provide the name, composition, source and preparation method of the prescription based on the prescription database; and an intelligent analysis submodule, used to intelligently analyze the frequency of all medicinal materials, calculate the correlation between medicinal materials and the correlation between prescriptions, and obtain a prescription recommendation degree and a medicinal material correlation analysis table.

[0010] According to the present invention, a traditional Chinese medicine auxiliary diagnosis and treatment system further includes a prescription evaluation module, which comprises: a doctor evaluation submodule, used to receive evaluation data of related prescriptions by doctors based on their own clinical experience when prescribing, wherein the related prescriptions are output by the symptom diagnosis module; a data parsing submodule, used to classify the recommendation level of the related prescriptions according to the recommendation level of the prescriptions and a set threshold; and a traditional Chinese medicine submodule, used to measure whether the source of the target prescription is a recognized classic book in the field of traditional Chinese medicine.

[0011] This invention provides a TCM-assisted diagnosis and treatment method, comprising: performing keyword parsing on symptom information text describing patient symptoms to obtain symptom vocabulary; if the symptom vocabulary exists, obtaining a prescription associated with the symptom corresponding to the symptom vocabulary; performing correlation analysis on the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials; obtaining the recommendation degree of the prescription based on the correlation degree of the associated medicinal materials, and outputting a target prescription according to the recommendation degree.

[0012] According to a TCM-assisted diagnosis and treatment method provided by the present invention, after performing keyword parsing on the symptom information text describing the patient's symptoms, the method further includes: if the symptom vocabulary does not exist, obtaining and outputting the set symptom data from the database to display the set symptoms and diagnosis and treatment references to medical personnel, wherein the set symptom data includes the set symptom name, TCM analysis, TCM treatment, and reference information.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the above-described TCM auxiliary diagnosis and treatment methods.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described TCM auxiliary diagnosis and treatment methods.

[0015] The TCM-assisted diagnosis and treatment method, system, electronic device, and non-transitory computer-readable storage medium provided by this invention obtain related prescriptions by performing keyword analysis on symptom description text, select related medicinal materials based on the related prescriptions, obtain the prescription recommendation degree based on the related medicinal materials, and output the target prescription according to the recommendation degree, thereby realizing intelligent diagnosis and treatment of TCM-assisted diagnosis and treatment.

[0016] Specifically, the technical solution of this invention performs keyword analysis on symptom description text, and then manages and further analyzes the prescriptions and medicinal materials obtained from the resulting symptom vocabulary to determine the recommendation level of each prescription. This completes the process of intelligently generating prescriptions based on symptom description text and a prescription database. This technical solution offers intelligent symptom diagnosis and intelligent prescription recommendation, assisting doctors in achieving efficient and accurate symptom diagnosis and prescription writing. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the TCM auxiliary diagnosis and treatment method provided by the present invention;

[0019] Figure 2 This is a schematic diagram of the workflow of the TCM auxiliary diagnosis and treatment system provided by the present invention;

[0020] Figure 3 This is a schematic diagram of the workflow of the symptom diagnosis module provided by the present invention;

[0021] Figure 4 This is a schematic diagram of the workflow of the prescription recommendation module provided by the present invention;

[0022] Figure 5 This is one of the schematic diagrams of the display interface of the TCM auxiliary diagnosis and treatment system provided by the present invention;

[0023] Figure 6 This is the second schematic diagram of the display interface of the TCM auxiliary diagnosis and treatment system provided by the present invention;

[0024] Figure 7This is the third schematic diagram of the display interface of the TCM auxiliary diagnosis and treatment system provided by the present invention;

[0025] Figure 8 This is the fourth schematic diagram of the display interface of the TCM auxiliary diagnosis and treatment system provided by the present invention;

[0026] Figure 9 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0028] The terminology used in one or more embodiments of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of the invention. The singular forms “a,” “described,” and “the” as used in one or more embodiments of the invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of the invention refers to and includes any or all possible combinations of one or more associated listed items.

[0029] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of the present invention, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of the present invention, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0030] The exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] like Figure 1 The diagram shown is a flowchart of a TCM-assisted diagnostic and treatment method according to an embodiment of the present invention. The method provided in this embodiment can be executed by any electronic device with computer processing capabilities, such as a terminal or server. Figure 1 As shown, this TCM-assisted diagnostic and treatment method includes:

[0032] Step 102: Perform keyword parsing on the symptom information text describing the patient's symptoms to obtain symptom vocabulary.

[0033] Specifically, natural language processing technology can be used for keyword parsing to avoid misunderstandings caused by inaccurate symptom descriptions in the symptom information text.

[0034] Step 104: If symptom words exist, obtain the prescription associated with the symptom corresponding to the symptom words.

[0035] Specifically, based on the intelligent association matching algorithm, information on one or more prescriptions for treating this symptom can be obtained.

[0036] Step 106: Perform a correlation analysis on the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the related medicinal materials associated with the symptoms.

[0037] Specifically, based on prescription information obtained from the prescription database, the frequency of all medicinal materials associated with the above symptoms can be obtained, and then the correlation degree of medicinal materials can be calculated. This correlation degree of medicinal materials is used to measure the degree of treatability between medicinal materials and symptoms.

[0038] Step 108: Obtain the recommendation level of the prescription based on the correlation of the related medicinal materials, and output the target prescription according to the recommendation level.

[0039] Specifically, related medicinal materials are categorized according to their degree of association, resulting in a set of designated medicinal materials. The medicinal materials constituting a prescription are then grouped into a prescription medicinal material set. Based on the Jaccard coefficients of the medicinal materials in both the designated and prescription medicinal material sets, the recommendation level of the prescription can be obtained. The recommendation level describes how well the prescription matches the current symptoms. After sorting the prescriptions in descending order of recommendation level, doctors can use this recommendation level as a reference when prescribing medication.

[0040] For example, the most recommended prescription can be chosen as the base prescription. Doctors can select a highly recommended prescription as the base prescription, modify the types of medicinal materials, increase or decrease the dosage of medicinal materials, and add information such as precautions for use before prescribing a treatment prescription for the current symptoms.

[0041] In the technical solution of this invention embodiment, keyword analysis is performed on the symptom description text, and prescription management and further analysis of prescription herbs are conducted on the obtained symptom vocabulary to obtain the recommendation degree of each prescription, thus completing the process of intelligent prescription generation based on symptom description text and prescription database. This technical solution has the effects of intelligent symptom diagnosis and intelligent prescription recommendation, which can assist doctors in completing efficient and accurate symptom diagnosis and prescription writing. In this invention embodiment, the prescription database can be simply referred to as the database.

[0042] After step 102, if the symptom vocabulary does not exist, the set symptom data in the database is retrieved and output to display the set symptoms and treatment references to medical personnel. The set symptom data includes the set symptom name, TCM analysis, TCM treatment, and reference information.

[0043] Specifically, setting symptoms refers to symptoms that occur frequently in daily diagnosis and treatment. For example, symptoms that are searched more than a set threshold in the database can be selected as set data. The data for setting symptoms is called set symptom data.

[0044] The TCM-assisted diagnosis and treatment method provided by this invention obtains related prescriptions by performing keyword analysis on symptom description text, selects related medicinal materials based on the related prescriptions, obtains the prescription recommendation degree based on the related medicinal materials, and outputs the target prescription according to the recommendation degree, thus realizing intelligent diagnosis and treatment of TCM-assisted diagnosis and treatment.

[0045] The TCM auxiliary diagnosis and treatment system provided by the present invention is described below. The TCM auxiliary diagnosis and treatment system described below can be referred to in correspondence with the TCM auxiliary diagnosis and treatment method described above.

[0046] like Figure 2 As shown in the figure, an embodiment of the present invention provides a traditional Chinese medicine auxiliary diagnosis and treatment system, which includes:

[0047] The parsing module 202 is used to perform keyword parsing on the symptom information text describing the patient's symptoms to obtain symptom vocabulary.

[0048] Specifically, the parsing module 202 can use natural language processing technology to parse keywords in order to avoid misunderstandings caused by inaccurate symptom descriptions in the symptom information text.

[0049] The symptom diagnosis module 204 is used to obtain prescriptions associated with the symptoms corresponding to the symptom words when symptom words exist.

[0050] Specifically, the symptom diagnosis module 204 can obtain information on one or more prescriptions for treating the symptom based on an intelligent association matching algorithm.

[0051] The herbal analysis module 206 is used to perform correlation analysis between the herbs in the prescription and the symptoms, and to obtain the correlation degree of the herbs associated with the symptoms.

[0052] Specifically, the herbal analysis module 206 can obtain the frequency of all herbs associated with the above symptoms based on the prescription information obtained from the prescription database, and then calculate the herbal correlation degree, which is used to measure the degree of treatability between the herbs and the symptoms.

[0053] The prescription recommendation module 208 is used to obtain the recommendation degree of the prescription based on the correlation of related medicinal materials, and output the target prescription according to the recommendation degree.

[0054] Specifically, the prescription recommendation module 208 categorizes related medicinal materials according to their relevance, resulting in a set of prescribed medicinal materials. The medicinal materials constituting a prescription are then grouped into a prescription medicinal material set. Based on the Jaccard coefficients of the medicinal materials in both the set of prescribed medicinal materials and the prescription medicinal material set, the recommendation level of the prescription can be obtained. The recommendation level describes the degree to which the prescription matches the current symptoms. After sorting the prescriptions in descending order of recommendation level, doctors can use this recommendation level as a reference when prescribing medication.

[0055] In the technical solution of this invention, keyword analysis is performed on the symptom description text, and prescription management and further analysis of the medicinal materials in the obtained symptom vocabulary are conducted to obtain the recommendation degree of each prescription. This completes the process of intelligent prescription generation based on symptom description text and prescription database. This technical solution has the effects of intelligent symptom diagnosis and intelligent prescription recommendation, which can assist doctors in completing efficient and accurate symptom diagnosis and prescription writing.

[0056] Specifically, the parsing module uses natural language processing technology to parse the input text-based symptom information into related symptom terms, which is used to solve the problem of inaccurate symptom descriptions.

[0057] In this embodiment of the invention, the TCM auxiliary diagnosis and treatment system may further include an anomaly detection module 210, which is used to obtain and output the set symptom data in the database when the symptom vocabulary does not exist, so as to display the set symptoms and diagnosis and treatment reference to medical personnel. The set symptom data includes the set symptom name, TCM analysis, Chinese medicine treatment and reference information.

[0058] Specifically, when the parsing module fails to parse precise symptom terms, the TCM-assisted diagnosis and treatment system automatically switches to the anomaly detection module. The anomaly detection module's symptom data submodule can provide common symptom information, TCM analysis, Chinese medicine treatments, and reference information.

[0059] In this embodiment of the invention, the symptom diagnosis module is further configured to diagnose one or more prescriptions that can be used to treat the symptoms corresponding to the symptom words based on the intelligent association analysis algorithm. The prescription information is stored in the form of prescription information units, which include prescription name, prescription evaluation module, prescription composition, prescription source and prescription details.

[0060] The symptom diagnosis module intelligently matches and associates the parsed symptom terms to diagnose one or more prescriptions that can treat the symptom. The prescription name is used to clearly identify the prescription and prevent confusion. The prescription evaluation module evaluates the prescription information to improve the efficiency of auxiliary diagnosis. The prescription composition information clarifies the medicinal materials that make up the prescription. The prescription source information clarifies the origin of the prescription. Detailed prescription information is used to connect to the prescription recommendation module to achieve effective prescription writing.

[0061] In this embodiment of the invention, the medicinal material analysis module is also used to perform correlation analysis on the medicinal material information and prescription information to obtain the recommendation degree of each prescription, the correlation degree between various medicinal materials and symptoms, and the frequency of medicinal materials corresponding to symptoms.

[0062] The herbal medicine analysis module calculates the frequency and performs correlation analysis on all herbs associated with the symptom, constructing a set of herbs that can treat the symptom. In addition, the module can efficiently analyze the correlation between the specified herbs and the prescription, deriving a prescription recommendation index to provide intelligent data support for doctors when prescribing medications.

[0063] In this embodiment of the invention, the prescription recommendation module may include: a prescription provision submodule, used to provide the name, composition, source and preparation method of the prescription according to the prescription database; and an intelligent analysis submodule, used to intelligently analyze the frequency of all medicinal materials, calculate the correlation between medicinal materials and the correlation between prescriptions, and obtain a prescription recommendation degree and a medicinal material correlation analysis table.

[0064] Doctors can use the intelligent analysis results provided by the prescription recommendation module to prescribe new medications. The prescription recommendation module can also include a sub-module for prescription-specific information and a sub-module for saving prescriptions.

[0065] The prescription information submodule provides the prescription's name, ingredients, source, and preparation method, offering doctors basic information for prescribing.

[0066] The intelligent analysis submodule generates a medicinal herb association table and a prescription recommendation table. This table intelligently analyzes the frequency of all medicinal herbs, calculates the correlation between herbs, and analyzes the correlation between prescriptions, resulting in a medicinal herb analysis table. Doctors can refer to this table when prescribing new prescriptions to modify herb dosages, add herbs with high correlation, or remove herbs with low correlation. Furthermore, it provides a prescription recommendation index, used to evaluate prescriptions after intelligent analysis, assisting doctors in prescribing more efficiently.

[0067] The doctor's prescription module is used by doctors to prescribe new medications for patients.

[0068] The prescription saving submodule can save new prescriptions according to the doctor's instructions. The prescription saving submodule corresponds to the prescription button. When the doctor clicks the prescription button, the prescription saving submodule receives the doctor's instructions.

[0069] The prescription database can store and integrate all prescription information, providing prescription data support for the symptom diagnosis module.

[0070] The prescription evaluation module is a set of multiple indicators used to evaluate prescriptions, which can be used as a reference for doctors when prescribing.

[0071] Specifically, the prescription evaluation module may include a doctor evaluation submodule, a data analysis submodule, and a traditional Chinese medicine submodule.

[0072] The doctor evaluation submodule receives evaluation data from doctors based on their clinical experience when prescribing medications. These related medications are output by the symptom diagnosis module. Through this submodule, after receiving a recommendation for a related medication, doctors can evaluate it based on their clinical experience, categorizing it as positive, neutral, or negative.

[0073] The data analysis submodule is used to classify the recommendation level of related prescriptions based on their recommendation level and set thresholds. This submodule uses intelligent analysis algorithms to analyze and calculate the correlation between herbs and prescriptions related to the symptom, deriving indicators such as prescription recommendation level, herb frequency, and prescription correlation. Based on the different levels of recommendation, prescriptions are categorized as strongly recommended or moderately recommended, to assist doctors in prescribing medications.

[0074] The Traditional Chinese Medicine submodule can determine whether a related prescription originates from a recognized classic book in the field of Traditional Chinese Medicine. If the prescription originates from a recognized classic book in the field of Traditional Chinese Medicine, then the related prescription has a high degree of recognition within the field.

[0075] The prescription evaluation module is used to evaluate all prescriptions, which can help doctors prescribe new prescriptions more accurately and efficiently.

[0076] This TCM-assisted diagnosis and treatment system uses intelligent data analysis technology to fully explore data information such as the correlation between medicinal materials and the correlation between prescriptions, so as to realize the intelligent and efficient diagnosis and prescription of doctors.

[0077] like Figure 2As shown, after the symptom information text is input into the parsing module 202, the parsing module 202 outputs symptom terms to the symptom diagnosis module 204. The symptom diagnosis module 204 outputs a prescription to the herbal medicine analysis module 206, and the herbal medicine analysis module outputs the herbal medicine correlation to the prescription recommendation module 208 to obtain the final target prescription. The herbal medicine analysis module relies on the prescription database 212 for herbal medicine analysis. When the parsing module cannot output symptom terms, the anomaly detection module 210 can output the set symptoms and corresponding treatment methods.

[0078] like Figure 3 As shown, in one embodiment, a symptom is input into the symptom diagnosis module, which can output one or more prescriptions. The output prescriptions are displayed in the form of prescription information units. The prescription information unit 301 includes a prescription name 301, a prescription evaluation module 302, the prescription's indications 303, the prescription's source 304, and detailed prescription information 305.

[0079] The prescription name is a treatment recommended by the symptom diagnosis module based on an intelligent association algorithm. The prescription evaluation module allows for multi-faceted and comprehensive evaluation of prescriptions, providing better assistance to doctors in prescribing medications. The prescription's indications refer to the symptoms that this prescription can treat in previous clinical cases. The prescription's source indicates the specific book from which the prescription originates. Detailed prescription information supplements the prescription information; this option allows access to the prescription recommendation module.

[0080] The prescription evaluation module includes a doctor evaluation submodule 306, a traditional Chinese medicine submodule 307, and a data analysis submodule 308. The doctor evaluation submodule allows doctors to evaluate related prescriptions recommended by the symptom diagnosis module based on their years of clinical experience, categorizing them as positive, neutral, or negative. This evaluation information is stored in the prescription database along with the prescription, facilitating subsequent work. The traditional Chinese medicine submodule evaluates prescriptions originating from classic books in the field of traditional Chinese medicine as originating from classic books, providing assistance to doctors in selecting prescriptions. The data analysis submodule is used to intelligently and efficiently assist doctors in prescribing prescriptions. It uses cutting-edge algorithms to intelligently calculate and analyze the recommendation level of related prescriptions, categorizing them as strongly recommended or moderately recommended. If the calculated recommendation level is below a certain threshold, a decision is made not to recommend the prescription.

[0081] like Figure 4 As shown, the prescription recommendation module is used to prescribe new prescriptions for patients. Doctors can combine the results of intelligent data analysis to modify the information such as medicinal materials, dosages, and preparation methods in the original prescription, and generate new prescriptions for patients.

[0082] The prescription recommendation module 208 includes a prescription inherent information submodule 401, an intelligent analysis submodule 406, a prescription provision submodule 402, and a prescription saving submodule 403.

[0083] The prescription recommendation module contains the prescription-specific information submodule, which stores the original prescription information obtained from the prescription database for related prescriptions, including prescription name, prescription composition, prescription indications, prescription source, and prescription preparation method.

[0084] The intelligent analysis submodule intelligently analyzes medicinal materials and prescriptions, which can determine the frequency of all medicinal materials associated with the input symptoms, and calculate the correlation degree I of the medicinal materials based on this frequency. a Used to measure the degree of treatability between medicinal materials and symptoms, I a The calculation formula is as follows:

[0085]

[0086] Where 'a' represents a certain medicinal material, 'i' is a natural number, and 'k' represents a certain prescription, for a total of n types, k i m represents the number of times herb 'a' appears in the prescription. i This represents the total number of times all medicinal materials appear in the prescription. Multiplying by 100 indicates that the correlation value is normalized to the range [0,10].

[0087] The prescription recommendation module categorizes all medicinal materials associated with the input symptoms based on their relevance. The top 20% of medicinal materials are classified as "set-up" medicinal materials, the bottom 20% as "low-frequency" medicinal materials, and the rest as "medium-frequency" medicinal materials.

[0088] Construct a set A of the medicinal materials of the specified type in symptom j. j The medicinal material data in the prescription i that can treat symptom j, output by the symptom diagnosis module, are constructed into a set B. i，j The recommendation level of a prescription is measured by the number of different types of medicinal materials that make up the prescription and the Jaccard coefficient of each material. The prescription recommendation module can calculate the recommendation level of a prescription according to the following formula:

[0089]

[0090] Among them, R i The recommendation level of prescription i is represented by the medicinal material analysis module. All prescription information units are then sorted from highest to lowest recommendation level, based on the recommendation level R. i Based on the differences, the prescriptions are rated and recommended, with a recommendation level R. i When the recommendation score is 10, the prescription is strongly recommended; when the recommendation score is in the range of [5, 10], the prescription is moderately recommended; otherwise, no recommendation rating is given.

[0091] like Figure 5 The image shows the analysis interface of the Traditional Chinese Medicine (TCM) auxiliary diagnosis and treatment system according to an embodiment of the present invention. Before querying prescriptions, intelligent analysis is performed on all data in the prescription database. This intelligent analysis includes global prescription analysis and herb correlation analysis. Global prescription analysis can determine the total number of existing prescriptions in the database, the number of existing prescriptions originating from classic books, the number of existing prescriptions originating from folk remedies and secret prescriptions, and the number and percentage of existing prescriptions with a recommendation level of 10. Herb correlation analysis can determine the types of all herbs in the prescription database, their correlation degree, and the quantity of herb varieties. The above analysis data is then used to construct a herb correlation table to assist doctors in prescribing medications.

[0092] like Figure 6 As shown, in the TCM-assisted diagnosis and treatment system of this invention, after entering the query "headache" in the query interface, the left area consists of multiple prescription information units to display recommended prescriptions. The prescription information units are arranged in descending order of prescription recommendation level. For example, from highest to lowest, they could be "Da Chuanxiong Wan," "Fangfeng Cangzhu Tang," "Huaban San," "Xiaoshu Yuan," and "Chonghe Lingbao Yin." Each prescription information unit can contain the prescription name, prescription evaluation badge, prescription indications, and detailed prescription information.

[0093] The prescription evaluation badge is a display format within the prescription evaluation module, including prescription recommendation level, prescription source, and doctor's evaluation. For "Da Chuan Xiong Wan," the evaluation badges are "Classic Book," "Positive Review," and "Highly Recommended."

[0094] The right-hand area consists of units such as global prescription analysis, medicinal material correlation analysis, and unit conversion table.

[0095] The global prescription analysis is used to analyze all prescription data recommended by the symptom diagnosis module for a specific symptom. In this figure, the input symptom is "headache," and the global prescription analysis shows that 118 prescriptions can be recommended. Among them, 4 prescriptions have a recommendation score of 10, accounting for 3.39%. 14 prescriptions are from classic books, accounting for 11.86%, and 7 prescriptions are from folk remedies or secret recipes, accounting for 5.93%.

[0096] Herbal association analysis is used to analyze the frequency of the constituent herbs in all prescriptions recommended by the symptom diagnosis module under a certain symptom and the degree of association with that symptom. In this figure, the input symptom is "headache". The herbal association analysis shows that there are 336 herbs that are associated with this symptom. Licorice has the strongest association with 6.024 and belongs to the set herbal herbs. Chuanxiong has the second strongest association with 3.494 and belongs to the set prescription.

[0097] The unit conversion table is used to compare and convert traditional Chinese medicine units with modern units of measurement for easy reference. Additionally, the left-hand area can be used to set up an "About Us" section, which provides a brief introduction to the research team behind this invention.

[0098] When the input symptom information is too coarse for the parsing module to be interpreted into specific symptom terms, the system will automatically enter the interface corresponding to the anomaly detection module. This interface includes a symptom data setting unit, which can be used to provide information on common symptoms, TCM analysis, TCM treatment, and reference. The displayed information is "The input symptom did not yield appropriate symptom information. Please refer to the following set symptom information." The set symptoms include "clearing heat and detoxifying," "promoting blood circulation and removing blood stasis," "traumatic injuries," "sore throat," "abdominal pain," and "cough." If the symptom "promoting blood circulation and removing blood stasis" is selected in the image, the detailed interpretation of "TCM treatment" and "reference" will be provided.

[0099] like Figure 7 The diagram shown is a prescription-generating interface of the TCM auxiliary diagnosis and treatment system according to an embodiment of the present invention. Clicking on the prescription details in the prescription information unit will bring you to this display interface, which includes a built-in information unit, a medicinal material analysis area, a doctor's prescription area, and a prescription button.

[0100] Doctors can modify the composition and dosage of herbs in the original prescription in the doctor's prescription area based on the prescription recommendation rate and herb correlation analysis in the herb analysis area, and then save the new prescription to their local device via the prescription button. The doctor's prescription area is where doctors edit new prescriptions. In this area, doctors can modify the types of herbs, increase or decrease the dosages, and add information such as precautions for prescription use, based on the results of the aforementioned intelligent analysis.

[0101] like Figure 7 As shown in the image, a doctor prescribes a new medication for a patient with headache symptoms. Based on the intelligent analysis, the prescription recommendation rate is 10, and the doctor decides to use Da Chuan Xiong Wan as the main ingredient. According to the correlation analysis of medicinal materials, the doctor adds 100 grams of licorice, the most correlated ingredient, and reduces the dosage of gastrodia by 20 grams. In the precautions, the doctor reminds the patient to soak their feet in warm water before going to bed every day and to reduce staying up late.

[0102] like Figure 8 As shown, the current screen displays a new prescription issued by the doctor. After issuing a new prescription, it can be saved locally.

[0103] The TCM-assisted diagnosis and treatment system provided by this invention obtains related prescriptions by performing keyword analysis on symptom description text, selects related medicinal materials based on the related prescriptions, obtains the recommendation degree of the prescription based on the related medicinal materials, and outputs the target prescription according to the recommendation degree, thus realizing intelligent diagnosis and treatment of TCM-assisted diagnosis and treatment.

[0104] Figure 9 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 9 As shown, the electronic device may include a processor 910, a communication interface 920, a memory 930, and a communication bus 990. The processor 910, communication interface 920, and memory 930 communicate with each other via the communication bus 990. The processor 910 can call logical instructions in the memory 930 to execute a traditional Chinese medicine (TCM) auxiliary diagnosis and treatment method. This method includes: parsing keywords from symptom information text describing patient symptoms to obtain symptom vocabulary; if the symptom vocabulary exists, obtaining a prescription associated with the symptom corresponding to the symptom vocabulary; performing a correlation analysis between the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials; obtaining the recommendation degree of the prescription based on the correlation degree of the associated medicinal materials, and outputting a target prescription according to the recommendation degree.

[0105] Furthermore, the logical instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0106] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the TCM auxiliary diagnosis and treatment method provided by the above methods, the method comprising: performing keyword parsing on symptom information text describing patient symptoms to obtain symptom vocabulary; if the symptom vocabulary exists, obtaining a prescription associated with the symptom corresponding to the symptom vocabulary; performing correlation analysis on the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials associated with the symptoms; obtaining the recommendation degree of the prescription based on the correlation degree of the associated medicinal materials, and outputting a target prescription according to the recommendation degree.

[0107] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned TCM auxiliary diagnosis and treatment methods. The method includes: performing keyword parsing on symptom information text describing patient symptoms to obtain symptom vocabulary; if the symptom vocabulary exists, obtaining a prescription associated with the symptom corresponding to the symptom vocabulary; performing correlation analysis on the medicinal materials in the prescription and the symptoms to obtain the correlation degree of the associated medicinal materials; obtaining the recommendation degree of the prescription based on the correlation degree of the associated medicinal materials, and outputting a target prescription according to the recommendation degree.

[0108] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A TCM-assisted diagnostic and treatment system, characterized in that, include: The parsing module is used to parse keywords from the symptom information text describing the patient's symptoms to obtain symptom vocabulary; The symptom diagnosis module is used to obtain a prescription associated with the symptom corresponding to the symptom when the symptom term exists; The herbal medicine analysis module is used to perform correlation analysis between the herbs in the prescription and the symptoms, and to obtain the correlation degree of the herbs associated with the symptoms; the correlation degree is calculated based on the frequency of each herbal medicine appearing in prescriptions associated with symptoms corresponding to the symptom words; The prescription recommendation module is used to obtain the recommendation degree of the prescription based on the correlation degree of the related medicinal materials, and output the target prescription according to the recommendation degree; Specifically, the prescription recommendation module is used for: The related medicinal materials are divided according to their degree of correlation to obtain a set of medicinal materials; The medicinal materials in the prescriptions associated with the symptoms corresponding to the symptom words are combined into a prescription material set; The recommendation level of the prescription is calculated based on the Jaccard coefficient between the set of medicinal materials and the set of medicinal materials in the prescription.

2. The system according to claim 1, characterized in that, The system also includes an anomaly detection module, which is used to obtain and output the set symptom data in the database when the symptom vocabulary does not exist, so as to display the set symptoms and treatment references to medical personnel. The set symptom data includes the set symptom name, traditional Chinese medicine analysis, traditional Chinese medicine treatment, and reference information.

3. The system according to claim 1, characterized in that, The symptom diagnosis module is also used to diagnose one or more prescriptions that can be used to treat the symptoms corresponding to the symptom words based on the intelligent association analysis algorithm. The prescription information is stored in the form of prescription information units, which include prescription name, prescription evaluation module, prescription composition, prescription source and prescription details.

4. The system according to claim 3, characterized in that, The medicinal material analysis module is also used to perform correlation analysis between the medicinal material information and the prescription information to obtain the recommendation degree of each prescription, the correlation degree between each medicinal material and the symptom, and the frequency of the medicinal material corresponding to the symptom.

5. The system according to claim 1, characterized in that, The prescription recommendation module includes: The prescription provision submodule is used to provide the name, composition, source, and preparation method of the prescription based on the prescription database; The intelligent analysis submodule is used to intelligently analyze the frequency of all medicinal materials, calculate the correlation between medicinal materials and the correlation between prescriptions, and obtain prescription recommendation and medicinal material correlation analysis tables.

6. The system according to claim 1, characterized in that, The system also includes a prescription evaluation module, which includes: The doctor evaluation submodule is used to receive evaluation data of related prescriptions by doctors based on their own clinical experience when prescribing medications, wherein the related prescriptions are output by the symptom diagnosis module; The data parsing submodule is used to classify the recommendation level of the associated prescriptions based on the recommendation level of the prescriptions and the set threshold. The Traditional Chinese Medicine submodule is used to determine whether the source of the target prescription is a recognized classic book in the field of Traditional Chinese Medicine.

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