Clinical diagnosis auxiliary system based on meridian data

Abstract

The invention discloses a clinical examination auxiliary system based on meridian data. Comprising a meridian prescription relation database used for storing meridian prescription-based dialectical data, and the meridian prescription-based dialectical data are associated data of diseases, meridian prescriptions and dialectical results obtained by inspection diagnosis, smelling diagnosis, inquiry diagnosis and cut diagnosis suitable for the meridian prescriptions; the pre-diagnosis module is used for acquiring pre-diagnosed disease syndromes obtained through inspection diagnosis, listening diagnosis and inquiry diagnosis and submitting the pre-diagnosed disease syndromes to the cut diagnosis recommendation module; and the cut diagnosis recommendation module is used for matching the pre-diagnosed disease syndromes with the applicable disease syndromes in the meridian relation database, and recommending the successfully matched cut diagnosis judgment based on the meridian differentiation data and the differentiation result to the user according to the matching degree. The method assists in improving the accuracy of the cutting diagnosis, reducing the difficulty of the cutting diagnosis, and reducing the limitation of the cognitive level and the cutting diagnosis state of the physician.

Description

Technical Field

[0001] The present invention belongs to the field of big data, and more specifically, relates to a palpation auxiliary system based on classical prescription data. Background Art

[0002] TCM syndrome differentiation is the core method of TCM diagnosis and treatment of diseases. It conducts a comprehensive analysis of the patient's symptoms, physical signs, tongue, pulse and other information to identify the cause, pathogenesis, location and nature of the disease, thus providing a basis for formulating personalized treatment plans.

[0003] Doctors collect information about patients' symptoms, physical signs, medical history, etc. through inspection, auscultation, questioning, and palpation. Inspection includes observing the patient's complexion, tongue coating, pulse, etc.; auscultation includes listening to the patient's voice, breathing, cough, etc.; questioning includes asking about the patient's symptoms, medical history, diet, sleep, etc.; palpation includes touching the patient's pulse and pressing parts of the body, etc.

[0004] Among the four diagnostic methods of TCM, namely, observation, auscultation, questioning and palpation, the questioning involves the interaction between doctors and patients, which actually involves the interaction between professionals and non-professionals. Since patients lack medical knowledge, they cannot accurately understand the key points of the questions raised by doctors, cannot accurately express their own symptoms, and state a lot of irrelevant information. Some patients even have hallucinations and form false information due to the torture of illness. The questioning is the most time-consuming. Palpation requires doctors to accumulate a lot of clinical experience and be familiar with medical principles. It is the most difficult diagnostic method to accurately diagnose and the most characteristic of TCM among the four diagnostic methods. In general, among the four diagnostic methods, palpation generally requires professional TCM practitioners to perform it, while the data collection of observation, auscultation and questioning is not difficult, and can be confirmed by patients themselves under the guidance of assistants trained in TCM or under prompts and guidance.

[0005] Generally, TCM syndrome differentiation diagnosis requires the TCM physician to judge the cause of the patient's illness based on a large amount of information after the doctor conducts the four examinations of observation, auscultation, questioning and palpation, and prescribe the right medicine. Due to the complexity of the human body and the variety of causes of disease, this diagnostic method requires a very high level of experience from the doctor and is difficult to promote on a large scale. Summary of the invention

[0006] In response to the above defects or improvement needs of the prior art, the present invention provides a palpation assistance system based on classical prescription data, the purpose of which is to use the application data of classical prescriptions in long-term medical treatment to associate the patient's symptoms and syndrome differentiation results, obtain the most likely pulse and palpation results, provide reference for doctors, reduce the difficulty of pulse identification, and improve the accuracy of pulse identification, thereby solving the technical problems that doctors currently need to rely entirely on hand feel and experience to identify pulses with subtle changes, which makes palpation difficult, is limited by doctors' experience, and the accuracy cannot be guaranteed.

[0007] To achieve the above-mentioned purpose, according to one aspect of the present invention, a palpation auxiliary system based on classical prescription data is provided, comprising a classical prescription relationship database, a pre-diagnosis module, and a palpation recommendation module;

[0008] The classical prescription relationship database is used to store syndrome differentiation data based on classical prescriptions, wherein the syndrome differentiation data based on classical prescriptions are disease syndromes obtained through inspection, auscultation, questioning, and palpation applicable to the classical prescriptions, classical prescriptions, and syndrome differentiation results association data, wherein the syndrome differentiation data based on classical prescriptions include applicable disease syndromes, classical prescriptions, palpation judgments, and syndrome differentiation, wherein the applicable disease syndromes are disease syndromes obtained through inspection, auscultation, and questioning;

[0009] The pre-diagnosis module is used to obtain the pre-diagnosis disease symptoms obtained through inspection, auscultation and questioning, and submit the pre-diagnosis disease symptoms to the palpation recommendation module;

[0010] The palpation recommendation module is used to match the pre-diagnosed disease with the applicable disease in the classical prescription relationship database, and recommend the palpation judgment and syndrome differentiation results of the successfully matched classical prescription-based syndrome differentiation data to the user according to the matching degree.

[0011] Preferably, the palpation auxiliary system based on classical prescription data further includes a prescription recommendation module;

[0012] The palpation recommendation module is further used to obtain the palpation judgment confirmed by the user, and submit the pre-diagnosed disease and the palpation judgment to the prescription recommendation module;

[0013] The prescription recommendation module is used to match the pre-diagnosed disease and the palpation judgment with the pre-diagnosed disease and the palpation judgment in the classical prescription relationship database, obtain the corresponding classical prescription based on the classical prescription syndrome differentiation data and recommend it to the user;

[0014] In a preferred embodiment, the prescription recommendation module recommends other syndromes based on the syndrome differentiation data of the classical prescription and the addition and subtraction schemes of the classical prescription to the user.

[0015] Preferably, in the palpation auxiliary system based on classical prescription data, the syndrome differentiation data based on classical prescription is acquired in the following manner:

[0016] Collect data on the application of classical prescriptions, including the classical prescriptions, the diseases and syndromes for which the classical prescriptions are applicable, and the syndrome differentiations for which the classical prescriptions are applicable;

[0017] The diseases and syndromes to which the classical prescriptions are applicable are divided into those obtained through inspection, auscultation and questioning as applicable diseases and syndromes, and the judgments obtained through palpation as palpation judgments, so as to obtain syndrome differentiation data based on the classical prescriptions.

[0018] Preferably, in the palpation auxiliary system based on classical prescription data, the applicable diseases and syndromes in the classical prescription relationship database are divided into main syndromes and secondary syndromes.

[0019] Preferably, in the palpation assistance system based on classical prescription data, the palpation recommendation module calculates the matching degree according to the ratio of the number of main symptom matches and the number of concurrent symptom matches to the total number of main symptoms and concurrent symptoms applicable to the classical prescription; when the matching degree of a pre-diagnosed disease and syndrome with a piece of classical prescription-based syndrome differentiation data exceeds a preset threshold, the pre-diagnosed disease and syndrome are successfully matched with the classical prescription-based syndrome differentiation data.

[0020] Preferably, the palpation auxiliary system based on classical prescription data calculates the matching degree i according to the following method:

[0021] i=(m+c) / (M+C)*100%

[0022] Among them, m is the number of symptoms that match the main symptoms of the classical prescription; M is the number of symptoms that the classical prescription is applicable to; c is whether the prediagnosed symptoms match the concomitant symptoms applicable to the classical prescription. When there is a prediagnosed symptom that matches the concomitant symptoms applicable to the classical prescription, c is 1, otherwise it is 0; C is the concomitant symptoms applicable to the classical prescription. When the classical prescription has an applicable concomitant symptom, C is 1, otherwise it is 0.

[0023] Preferably, the pre-diagnosis module of the palpation auxiliary system based on classical prescription data provides users with colloquial expressions of diseases and symptoms for their confirmation, and associates the colloquial expressions of diseases and symptoms confirmed by users as standard pre-diagnosis diseases and symptoms.

[0024] Preferably, in the palpation auxiliary system based on classical prescription data, the pre-diagnosis module provides the user with spoken expressions of the disease symptoms for confirmation multiple times until the user confirms that there are no more disease symptoms.

[0025] Preferably, the pre-diagnosis module of the palpation auxiliary system based on classical prescription data provides the user with a colloquial expression of the disease for the first time for the user to confirm, according to the patient's past medical history, in accordance with the principle that the higher the possibility of the disease, the higher the probability of providing the user with a colloquial expression of the disease for the first time; and / or

[0026] The pre-diagnosis module provides the user with a colloquial expression of the disease for the first time for the user to confirm, according to the principle that the higher the probability of the disease occurring in the population, the higher the probability of providing the user with a colloquial expression of the disease for the first time; and / or

[0027] According to the principle that the higher the probability of association between the disease and the patient's self-report, the higher the probability of providing the user with the spoken expression of the disease for the first time, the user is provided with the spoken expression of the disease for the first time for confirmation;

[0028] Until the user confirms at least one colloquial expression of the disease or symptom, the colloquial expression of the disease or symptom is provided to the user for the first time.

[0029] Preferably, the palpation assistance system based on classical prescription data, its pre-diagnosis module provides the user with a spoken expression of the disease and symptoms for confirmation this time according to the principle that the higher the probability of co-occurrence with the disease and symptoms collected from the user last time, the higher the probability of a spoken expression of the disease and symptoms for the user this time, except for the first time.

[0030] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0031] The present invention collects application data of classical prescriptions, utilizes long-term clinical application experience of classical prescriptions, associates inspection, medical questioning, symptoms and signs obtained through questioning, pulse diagnosis, and syndrome differentiation results, and after obtaining a preliminary diagnosis through inspection, medical questioning, and symptoms and signs obtained through questioning, associates the most likely pulse and syndrome differentiation results and provides them to physicians for reference, assisting physicians in reducing the difficulty of identification during palpation and prompting key pulse details that need to be identified, thereby assisting in improving the accuracy of palpation, reducing the difficulty of palpation, and reducing the limitations of physicians' cognitive level and palpation status.

[0032] The preferred solution is to use colloquial expressions for pre-diagnosis, link the diseases and syndromes confirmed by colloquial expressions with standard pre-diagnosis diseases and syndromes, obtain comprehensive and accurate pre-diagnosis results as much as possible, improve the accuracy of matching pulse and syndrome differentiation results, and further optimize the recommended prescriptions. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the structure of the palpation auxiliary system based on classical prescription data provided by the present invention. DETAILED DESCRIPTION

[0034] 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 the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0035] TCM prescriptions refer to the classic prescriptions recorded in TCM classics. These prescriptions have been tested in clinical practice for thousands of years and have definite curative effects and wide application value. The application of prescriptions must follow the principle of syndrome differentiation and treatment. According to the patient's symptoms, signs, tongue, pulse, etc., a comprehensive analysis should be conducted to identify the syndrome type of the disease, and then the appropriate prescription should be selected for treatment. For example, if the patient has symptoms such as aversion to cold and fever, no sweating, headache, body pain, and floating pulse, it can be identified as solar typhoid fever, and Mahuang Decoction should be used for treatment; if fever, sweating, aversion to wind, floating pulse, etc. are present, it can be identified as solar stroke, and Guizhi Decoction should be used for treatment.

[0036] Therefore, a lot of data on the application of classical prescriptions have been accumulated in the clinical data of traditional Chinese medicine. The data on the application of classical prescriptions effectively associates the diseases and symptoms of the four diagnoses of traditional Chinese medicine with the data on the results of traditional Chinese medicine syndrome differentiation. The present invention utilizes the association between the application data of classical prescriptions and the results of syndrome differentiation, and prompts the possible diseases and syndrome differentiation results of palpation based on the inspection, questioning, and questioning data, so as to provide auxiliary diagnosis information for traditional Chinese medicine practitioners to perform palpation, narrow the scope of syndrome differentiation, improve the accuracy of syndrome differentiation, and save syndrome differentiation time. More conveniently, the auxiliary system of the present invention, which calculates and matches the classical prescription data based on disease and syndrome data, takes the classical prescription (a group of traditional Chinese medicines) to solve the main symptoms, concurrent symptoms, and all or the main symptoms of the syndrome as the starting point, thereby greatly reducing the calculation parameters and their related variable functions, which not only simplifies the calculation method and reduces the amount of calculation, but also greatly improves the accuracy of the calculation results. Specifically:

[0037] The palpation auxiliary system based on classical prescription data provided by the present invention comprises a classical prescription relationship database, a pre-diagnosis module, a palpation recommendation module, and preferably also comprises a prescription recommendation module.

[0038] The classical prescription relationship database is used to store syndrome differentiation data based on classical prescriptions, wherein the syndrome differentiation data based on classical prescriptions are disease syndromes obtained through inspection, auscultation, questioning, and palpation applicable to the classical prescriptions, classical prescriptions, and syndrome differentiation result association data, wherein the syndrome differentiation data based on classical prescriptions include applicable disease syndromes, classical prescriptions, palpation judgments, and syndrome differentiation, wherein the applicable disease syndromes are disease syndromes obtained through inspection, auscultation, and questioning; and the syndrome differentiation data are obtained in the following manner:

[0039] Collect data on the application of classical prescriptions, including the classical prescriptions, the diseases and syndromes for which the classical prescriptions are applicable, and the syndrome differentiations for which the classical prescriptions are applicable;

[0040] The diseases and syndromes to which the classical prescriptions are applicable are divided into those obtained through inspection, auscultation and questioning as applicable diseases and syndromes, and the judgments obtained through palpation as palpation judgments, so as to obtain syndrome differentiation data based on the classical prescriptions.

[0041] In a preferred embodiment, the applicable diseases and syndromes in the classical prescription relationship database are divided into main syndromes and concurrent syndromes.

[0042] The pre-diagnosis module is used to obtain the pre-diagnosis disease symptoms obtained through inspection, auscultation and questioning, and submit the pre-diagnosis disease symptoms to the palpation recommendation module;

[0043] In a preferred embodiment, the pre-diagnosis module provides the user with colloquial expressions of the disease for confirmation, and associates the colloquial expressions of the disease confirmed by the user as standard pre-diagnosed disease; the pre-diagnosis module provides the user with colloquial expressions of the disease for confirmation multiple times until the user confirms that there are no more disease; specifically, the pre-diagnosis module provides the user with the colloquial expression of the disease for the first time for confirmation according to the patient's previous medical history, on the principle that the higher the possibility of the disease, the higher the probability of providing the colloquial expression of the disease to the user for the first time, or provides the user with the colloquial expression of the disease for the first time according to the principle that the higher the probability of the disease in the population, the higher the probability of providing the user with the colloquial expression of the disease. The pre-diagnosis module provides the user with the colloquial expression of the disease for the first time for confirmation according to the principle of the higher the probability of association between the disease and the patient's self-report, or according to the principle that the higher the probability of association between the disease and the patient's self-report, the higher the probability of providing the colloquial expression of the disease for the first time for confirmation, until the user confirms at least one colloquial expression of the disease as the first colloquial expression of the disease for the user; the pre-diagnosis module provides the user with the colloquial expression of the disease for the user to confirm this time according to the principle that the higher the probability of co-occurrence with the disease collected last time, the higher the probability of providing the colloquial expression of the disease for the user this time. The user of the pre-diagnosis module can be the patient himself, his family or a physician with diagnosis and treatment experience.

[0044] The palpation recommendation module is used to match the pre-diagnosed disease with the applicable disease in the classical prescription relation database, and recommend the palpation judgment and the syndrome differentiation result of the successfully matched classical prescription-based syndrome differentiation data to the user according to the matching degree; the palpation recommendation module is also used to obtain the palpation judgment confirmed by the user, and submit the pre-diagnosed disease and the palpation judgment to the prescription recommendation module;

[0045] In a preferred embodiment, the palpation recommendation module calculates the matching degree according to the ratio of the number of main symptom matches and the number of concurrent symptom matches to the total number of main symptom matches and concurrent symptom matches applicable to the classical prescription, and specifically calculates the matching degree i according to the following method:

[0046] i=(m+c) / (M+C)*100%

[0047] Among them, m is the number of symptoms that match the main symptoms of the classical prescription; M is the number of symptoms that the classical prescription is applicable to; c is whether the prediagnosed symptoms match the concomitant symptoms applicable to the classical prescription. When there is a prediagnosed symptom that matches the concomitant symptoms applicable to the classical prescription, c is 1, otherwise it is 0; C is the concomitant symptoms applicable to the classical prescription. When the classical prescription has an applicable concomitant symptom, C is 1, otherwise it is 0.

[0048] When the matching degree between the pre-diagnosed disease and syndrome differentiation data based on classical prescriptions exceeds a preset threshold, the pre-diagnosed disease and syndrome differentiation data based on classical prescriptions are successfully matched.

[0049] The prescription recommendation module is used to match the pre-diagnosed disease and the diagnosis with the pre-diagnosed disease and the diagnosis in the prescription relationship database, obtain the corresponding prescription based on the syndrome differentiation data of the prescription and recommend it to the user. In a preferred embodiment, the prescription recommendation module recommends other syndromes based on the syndrome differentiation data of the prescription and the addition and subtraction scheme of the prescription to the user.

[0050] The following are examples:

[0051] The palpation auxiliary system based on classical prescription data provided in this embodiment includes a classical prescription relationship database, a pre-diagnosis module, a palpation recommendation module, and preferably also includes a prescription recommendation module.

[0052] The classical prescription relationship database is used to store the syndrome differentiation data based on the classical prescriptions, the syndrome differentiation data based on the classical prescriptions are the disease syndromes obtained by inspection, auscultation, questioning and palpation, classical prescriptions, and syndrome differentiation result association data, the syndrome differentiation data based on the classical prescriptions include applicable disease syndromes, classical prescriptions, palpation judgment, and syndrome differentiation, the applicable disease syndromes are the disease syndromes obtained by inspection, auscultation and questioning; the syndrome differentiation data based on the classical prescriptions are obtained in the following manner:

[0053] Collect data on the application of classical prescriptions, including the classical prescriptions, the diseases and syndromes for which the classical prescriptions are applicable, and the syndrome differentiations for which the classical prescriptions are applicable;

[0054] According to the acquisition channels, the diseases and syndromes applicable to the classical prescriptions are divided into diseases and syndromes obtained through inspection, auscultation and questioning as applicable diseases and syndromes, and the judgments obtained through palpation as palpation judgments, so as to obtain syndrome differentiation data based on the classical prescriptions. Palpation judgments are pulse condition data.

[0055] The applicable disease syndromes described in the classical prescription relationship database are divided into main syndromes, concurrent syndromes, and other syndromes.

[0056] The data structure of the Jingfang database is shown in Table 1.

[0057] Table 1. Database of Jingfang

[0058]

[0059] In order to expand the content of the classical prescription relationship database, the present invention collects, identifies and organizes the classical prescription application data, including collecting the basic data of the classical prescription; collecting and organizing the classical prescription relationship data, including the classical prescription applicable syndrome data and identifying and dividing it into main syndrome data, concurrent syndrome data, or syndrome data, and supplementing the omitted or missing disease syndrome data in the description of the main syndrome in the classical prescription applicable syndrome in the TCM classics; collecting pulse data and supplementing the missing pulse data; collecting and organizing the classical prescription contraindication syndrome data and syndrome differentiation data.

[0060] The pre-diagnosis module is used to obtain the pre-diagnosis disease symptoms obtained through inspection, auscultation and questioning, and submit the pre-diagnosis disease symptoms to the palpation recommendation module;

[0061] The pre-diagnosis module provided in this embodiment provides the user with colloquial expressions of symptoms for confirmation, and associates the colloquial expressions of symptoms confirmed by the user as standard pre-diagnosed symptoms; the pre-diagnosis module provides the user with colloquial expressions of symptoms for confirmation multiple times until the user confirms that there are no more symptoms; specifically, the pre-diagnosis module collects symptoms with a high correlation degree from the patient's self-described symptom big data based on the patient's simple self-description of one or two symptoms, and at the same time, the pre-diagnosis module associates symptoms with a high probability of occurrence based on the patient's past medical history, and provides the user with the colloquial expressions of these symptoms for the first confirmation of the symptoms until the user confirms at least one colloquial expression of the symptoms as the first colloquial expression of the symptoms provided to the user; the pre-diagnosis module provides the user with the colloquial expressions of the symptoms for confirmation this time according to the principle that the higher the probability of co-occurrence with the user's symptoms collected last time, the higher the probability of the colloquial expression of the symptoms for the user this time.

[0062] In this embodiment, the disease information collection system of the present invention is composed of: 1. disease information collection terminal equipment (patient's mobile phone, etc.); 2. disease information pre-collection special disease database; 3. machine diagnosis special disease database; 4. machine diagnosis center and other parts.

[0063] The operation process of the disease information pre-collection system of the present invention is: 1. The patient logs in to the disease information pre-collection system of the present invention using a terminal device such as a personal mobile phone; 2. A medical questionnaire appears, and the patient fills in and submits the questionnaire; 3. The disease information enters the intelligent diagnosis center.

[0064] The disease information collection system of this embodiment is to establish a standardized disease database for consultation. The characteristics are: first, the disease database for consultation consists of disease names and disease names, which have a strict one-to-one correspondence with the disease names and disease names in the machine diagnosis disease database; second, the disease names in the machine diagnosis database are derived from traditional Chinese medicine classics and belong to professional terms. The disease names in the disease database for consultation are colloquial translations of professional terms. In other words, all diseases in the disease database for consultation are derived from traditional Chinese medicine classics.

[0065] The significance of the consultation-specific disease database is: 1. It allows patients to understand without ambiguity; 2. The "colloquial" disease and the "professional terminology" disease can be matched; 3. When a group of diseases that are described in some obscure diseases in traditional Chinese medicine classics appear, a new disease is automatically generated. It is actually a bridge for communication between patients and doctors (including machines). It avoids the transmission distortion of disease information and avoids the difference in the cognition of professional knowledge between patients and doctors that leads to poor communication.

[0066] The process is as follows:

[0067] The patient enters the disease information pre-collection system; the system displays the header of the medical questionnaire, and the patient fills in basic information such as gender and age, and then describes his or her symptoms in voice or text; the disease information collection system automatically extracts some disease symptoms or disease names from the disease database based on the patient's past medical history and other big data, and generates a personalized medical questionnaire for the patient. Its features are:

[0068] 1. The content in the personalized medical questionnaire, namely, the disease symptoms, includes both the disease symptoms expressed by the clinical symptom characteristics reported by the patient; the clinical symptom characteristics reported by the patient are vague, which point to multiple disease symptoms with higher probability; there are also possible disease symptoms associated with the clinical symptom characteristics reported by the patient; and the disease symptoms that the big data analysis machine believes the patient may have.

[0069] 2. The symptoms and signs in the medical questionnaire are described in popular language, but the wording is rigorous and standardized, the expression is accurate, and it is not easy to cause ambiguity.

[0070] 3. The process of patients filling out medical questionnaires is actually a process of re-examination and confirmation of their own medical symptoms. In addition, the description of the medical symptoms in the medical questionnaire is rigorous and easy to understand, so the medical questionnaires filled out by patients are more accurate.

[0071] 4. Personalized medical questionnaires can save time in filling out forms and avoid excessive consumption of patients’ patience and the resulting misselection of diseases.

[0072] In addition, the pre-diagnosis module of this embodiment has an image uploading function, and the patient can upload images of the tongue, lesion site, etc. taken by himself.

[0073] Specific examples include:

[0074] First recommended symptom: Recommend symptoms based on the patient's medical history and the patient's self-report, and provide colloquial expressions of symptoms for users to confirm: "cough", "fever"

[0075] After the user confirms the symptoms of "cough" and "fever", the system recommends the related symptoms of "cough" and "fever" for the patient to confirm: "headache, stiff neck, discomfort", "sweating", "no sweating", "body pain", "bone and joint pain", "itchy throat", "panting", "want to drink water", "don't want to drink water", "dry mouth", "not dry mouth", "fear of wind", "fear of cold", "dry retching", "hiccups", "low back pain", "white tongue coating", "red tongue without coating", "clear runny nose", "nasal congestion", "clear and thin white sputum", "yellow and thick sputum", "don't want to eat", "bloated lower abdomen", "bloating", "constipation", "diarrhea";

[0076] This process is repeated until the user confirms that there are no more symptoms. The acquired colloquial expressions of symptoms are matched with standard symptoms. The pre-diagnosis module of this embodiment finally extracts the pre-diagnosis symptoms: fever, cough, no sweating, joint pain, aversion to wind, aversion to cold, asthma, drooling, white tongue coating, nasal congestion, clear nasal discharge, itchy throat, and no thirst.

[0077] Palpation is transformed into questioning. Some of the contents of inspection and smell are already commonly implemented in the actual TCM clinic. For example, the color of urine and the smell of stool do not need to be observed or smelled by the doctor, and the patient can answer directly in the form of questioning; some inspection and smell require the help of others to answer, such as the peculiar smell of the patient's breath, which the patient often cannot smell by himself and needs to be told by others before answering; some can only be completed under the guidance of the pre-diagnosis module, such as tenderness at the Tianshu point, the patient does not know where the Tianshu point is, the patient only needs to click on the tenderness of Tianshu to display the image guidance with text description.

[0078] The pre-diagnosis module utilizes modern communication technology to convert the main contents of palpation in inspection, auscultation and palpation into a form of questioning and implement it online.

[0079] The palpation recommendation module is used to match the pre-diagnosed disease with the applicable disease in the classical prescription relation database, and recommend the palpation judgment and the syndrome differentiation result of the successfully matched classical prescription-based syndrome differentiation data to the user according to the matching degree; the palpation recommendation module is also used to obtain the palpation judgment confirmed by the user, and submit the pre-diagnosed disease and the palpation judgment to the prescription recommendation module;

[0080] This embodiment matches the pre-diagnosis data with the syndrome differentiation data based on classical prescriptions.

[0081] The palpation recommendation module calculates the matching degree according to the ratio of the number of matching main symptoms and the number of matching concomitant symptoms to the total number of main symptoms and concomitant symptoms applicable to the classical prescription, and specifically calculates the matching degree i according to the following method:

[0082] i=(m+c) / (M+C)*100%

[0083] Among them, m is the number of symptoms that match the main symptoms of the classical prescription; M is the number of symptoms that the classical prescription is applicable to; c is whether the pre-diagnosed symptoms match the secondary symptoms that the classical prescription is applicable to. When there is a pre-diagnosed symptom that matches the secondary symptoms that the classical prescription is applicable to, c is 1, otherwise it is 0; C is the secondary symptoms that the classical prescription is applicable to. When there is a secondary symptom that the classical prescription is applicable to, C is 1, otherwise it is 0. Generally, C ≤ 45% M.

[0084] Calculate the matching degree. The prescriptions that meet the preset threshold requirements of the matching degree are: Xiaoqinglong Decoction, Mahuang Decoction, Guizhi Houpu Xingzi Decoction as pre-selected prescriptions. Assuming that the disease data collected by the pre-diagnosis module has one or more matches with the concurrent syndromes and or syndromes in the prescription applicable syndrome, C = c = 1; otherwise C = c = 0; the matching prescription data and its dialectical data are calculated as shown in Table 2.

[0085] The results are sorted by matching degree as shown in Table 2:

[0086] Table 2 Matching degree sorting of Jingfang data

[0087]

[0088]

[0089] Note: The information in brackets indicates the diseases and syndromes that the classical prescriptions are applicable to and match the pre-diagnosed diseases and syndromes.

[0090] The palpation recommendation module recommends the above results to the doctor, prompting the doctor to confirm whether it is a "floating pulse". If it is a "floating pulse", it is necessary to further carefully identify whether the pulse is "tight" or "slow". Finally, after the doctor palpates, he confirms that the pulse is "floating and slow". The palpation recommendation module helps the doctor narrow down the possible pulse range and reduce the difficulty of pulse identification.

[0091] According to the matching status data, it prompts the pulse data applicable to the classical prescriptions that may need medical confirmation; the disease data that still needs further supplementation by the doctor for syndrome differentiation and the disease data that needs medical treatment.

[0092] The prescription recommendation module is used to match the pre-diagnosed disease and the palpation judgment with the pre-diagnosed disease and the palpation judgment in the classical prescription relationship database, obtain the corresponding classical prescription based on the syndrome differentiation data of the classical prescription and recommend it to the user. The prescription recommendation module recommends other syndromes based on the syndrome differentiation data of the classical prescription and the addition and subtraction scheme of the classical prescription to the user.

[0093] The normally displayed diseases and syndromes are the disease and syndrome data collected by the pre-diagnosis module and recommended to the auxiliary medical diagnosis module, which are successfully matched with the disease and syndrome data of the classical prescription applicable syndrome; black background text indicates that the classical prescription applicable syndrome should or may have disease and syndrome data but the patient's disease and syndrome data are missing. When the doctor diagnoses, the missing disease and syndrome data in the main syndrome will be supplemented by the medical diagnosis or confirmed, and the missing disease and syndrome data in the concurrent syndrome or concomitant syndrome can be directly ignored.

[0094] Other syndromes in black background refer to syndrome data that are included in the patient's syndrome data but are not within the scope of the applicable syndromes of the classical prescriptions. The doctor can choose to confirm or ignore them.

[0095] The pulse condition with black background is the pulse condition that may be seen in traditional Chinese medicine prescriptions. When the doctor clicks on the pulse condition name to confirm the pulse condition, the pulse condition will change to normal display with white background.

[0096] The contraindications for the use of classical prescriptions written in black need to be confirmed by the doctor. Once the doctor clicks on the existence of the contraindication disease or symptom, the classical prescription will exit the medical diagnosis module regardless of the matching status of the other disease or symptom data and pulse data of the classical prescription.

[0097] The medical diagnosis module is used to supplement, confirm and process the disease data and pulse data in the classical prescription differentiation recommended by the auxiliary medical diagnosis recommendation module, select the classical prescription or use the classical prescription as the base prescription to add or subtract according to the symptoms to form a medical diagnosis and medical record prescription.

[0098] It is used to supplement, confirm and process the disease data and pulse data in the classical prescription differentiation recommended by the auxiliary medical diagnosis recommendation module, select the classical prescription or use the classical prescription as the base prescription to add or subtract according to the symptoms to form a medical diagnosis and medical record prescription.

[0099] This embodiment recommends the diagnosis of palpation to the physician, who confirms the result of the palpation. For example, if the result of the palpation is that the pulse is floating and slow, "Guizhi Houpu Xingzi Decoction" is recommended, and its related syndrome differentiation "the exterior of the Taiyang disease is not resolved, and the purgation is slightly wheezing", and the contraindications "no sweating, sweating contraindications" are provided to the physician for reference. If there are other symptoms and prescription additions and subtractions, they are also pushed to the physician for reference.

[0100] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A palpation auxiliary system based on classical prescription data, characterized in that: Including the classic prescription relationship database, pre-diagnosis module, and palpation recommendation module; The classical prescription relationship database is used to store syndrome differentiation data based on classical prescriptions, wherein the syndrome differentiation data based on classical prescriptions are disease syndromes obtained through inspection, auscultation, questioning, and palpation applicable to the classical prescriptions, classical prescriptions, and syndrome differentiation results association data, wherein the syndrome differentiation data based on classical prescriptions include applicable disease syndromes, classical prescriptions, palpation judgments, and syndrome differentiation, wherein the applicable disease syndromes are disease syndromes obtained through inspection, auscultation, and questioning; The pre-diagnosis module is used to obtain the pre-diagnosis disease symptoms obtained through inspection, auscultation and questioning, and submit the pre-diagnosis disease symptoms to the palpation recommendation module; The palpation recommendation module is used to match the pre-diagnosed disease with the applicable disease in the classical prescription relationship database, and recommend the palpation judgment and syndrome differentiation results of the successfully matched classical prescription-based syndrome differentiation data to the user according to the matching degree.

2. The palpation auxiliary system based on classical prescription data as claimed in claim 1, characterized in that: It also includes a prescription recommendation module; The palpation recommendation module is further used to obtain the palpation judgment confirmed by the user, and submit the pre-diagnosed disease and the palpation judgment to the prescription recommendation module; The prescription recommendation module is used to match the pre-diagnosed disease and the palpation judgment with the pre-diagnosed disease and the palpation judgment in the classical prescription relationship database, obtain the corresponding classical prescription based on the classical prescription syndrome differentiation data and recommend it to the user; In a preferred embodiment, the prescription recommendation module recommends other syndromes based on the syndrome differentiation data of the classical prescription and the addition and subtraction schemes of the classical prescription to the user.

3. The palpation auxiliary system based on classical prescription data according to claim 1 or 2, characterized in that: The syndrome differentiation data based on classical prescriptions are obtained in the following manner: Collect data on the application of classical prescriptions, including the classical prescriptions, the diseases and syndromes for which the classical prescriptions are applicable, and the syndrome differentiations for which the classical prescriptions are applicable; The diseases and syndromes to which the classical prescriptions are applicable are divided into those obtained through inspection, auscultation and questioning as applicable diseases and syndromes, and the judgments obtained through palpation as palpation judgments, so as to obtain syndrome differentiation data based on the classical prescriptions.

4. The palpation auxiliary system based on classical prescription data according to claim 1 or 2, characterized in that: The applicable diseases and syndromes described in the classical prescription relationship database are divided into main syndromes and concomitant syndromes.

5. The palpation auxiliary system based on classical prescription data as claimed in claim 4, characterized in that: The palpation recommendation module calculates the matching degree according to the ratio of the number of main symptom matches and the number of concurrent symptom matches to the total number of main symptom matches and concurrent symptom matches applicable to the classical prescription; when the matching degree between the pre-diagnosed disease and a syndrome differentiation data based on the classical prescription exceeds a preset threshold, the pre-diagnosed disease and the syndrome differentiation data based on the classical prescription are successfully matched.

6. The palpation auxiliary system based on classical prescription data as claimed in claim 5, characterized in that: The matching degree i is calculated as follows: i=(m+c) / (M+C)*100% Among them, m is the number of symptoms that match the main symptoms of the classical prescription; M is the number of symptoms that the classical prescription is applicable to; c is whether the prediagnosed symptoms match the concomitant symptoms applicable to the classical prescription. When there is a prediagnosed symptom that matches the concomitant symptoms applicable to the classical prescription, c is 1, otherwise it is 0; C is the concomitant symptoms applicable to the classical prescription. When the classical prescription has an applicable concomitant symptom, C is 1, otherwise it is 0.

7. The palpation auxiliary system based on classical prescription data according to claim 1 or 2, characterized in that: The pre-diagnosis module provides the user with colloquial expressions of the disease for confirmation, and associates the colloquial expressions of the disease confirmed by the user as standard pre-diagnosis diseases.

8. The palpation auxiliary system based on classical prescription data as claimed in claim 7, characterized in that: The pre-diagnosis module provides the user with spoken expressions of the disease symptoms for confirmation multiple times until the user confirms that there are no more disease symptoms.

9. The palpation auxiliary system based on classical prescription data as claimed in claim 8, characterized in that: The pre-diagnosis module provides the user with a spoken expression of the disease for the first time for the user to confirm according to the patient's past medical history and the principle that the higher the possibility of the disease, the higher the probability of providing the spoken expression of the disease to the user for the first time; and / or The pre-diagnosis module provides the user with a colloquial expression of the disease for the first time for confirmation by the user according to the principle that the higher the probability of the disease occurring in the population, the higher the probability of providing the user with a colloquial expression of the disease for the first time; and / or According to the principle that the higher the probability of association between the disease and the patient's self-report, the higher the probability of providing the user with the spoken expression of the disease for the first time, the user is provided with the spoken expression of the disease for the first time for confirmation; Until the user confirms at least one colloquial expression of the disease or symptom, the colloquial expression of the disease or symptom is provided to the user for the first time.

10. The palpation auxiliary system based on classical prescription data according to claim 8, characterized in that: The pre-diagnosis module provides the user with a spoken expression of the disease for confirmation this time according to the principle that the higher the co-occurrence probability of the disease collected last time, the higher the probability of the spoken expression of the disease for the user this time, except for the first time.

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