Intelligent decision-making auxiliary diagnosis and treatment platform

Abstract

The invention discloses an intelligent decision-making auxiliary diagnosis and treatment platform, and the system comprises a user obtaining end which is used for a user to input own information and first medical data, obtained by a medical platform, of the user, the own information is identity card information of the user, and the first medical data is in-vivo medical data and in-vitro medical data of the user; the processor end of the medical platform is used for judging whether the user is an initial user or not based on the information of the user, obtaining initial disease information of the user based on the association degree between the first medical data of the user and the medical data of other users in the database when the user is the initial user, and sending the initial disease information to the server; the technical problems that at present, a patient is difficult to see a doctor, the patient lacks previous cases, and the disease cure rate is low are solved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent decision-making auxiliary diagnosis and treatment technology, and in particular to an intelligent decision-making auxiliary diagnosis and treatment platform. Background Art

[0002] In recent years, with the research and development of traditional Chinese medicine and people's trust in it, more and more patients are keen on it. However, there is a big gap between the number of traditional Chinese medicine doctors and patients. The number of doctors is far from meeting the needs of patients. In addition, the speed of doctors taking pulses and treating patients is slow, so that patients' diseases cannot be treated in time. Many patients forget their previous symptoms during the process of seeking medical treatment, so that doctors cannot prescribe the right medicine well, and the cure rate is reduced. Therefore, an intelligent decision-making auxiliary diagnosis and treatment platform is proposed to solve the current technical problems of patients' difficulty in seeing a doctor, patients' lack of previous cases, and low cure rate of diseases. Summary of the invention

[0003] The embodiment of the present invention provides an intelligent decision-making auxiliary diagnosis and treatment platform, which solves the current technical problems that it is difficult for patients to see a doctor, patients lack previous medical records, and the cure rate of diseases is low.

[0004] According to one aspect of an embodiment of the present invention, an intelligent decision-making auxiliary diagnosis and treatment platform is provided, and the system may include: a user acquisition end, a processor end of a medical platform, and a user receiving end.

[0005] The user acquisition end is used for the user to input his own information and the user's first medical data obtained by the medical platform, wherein the self-information is the user's ID card information, and the first medical data is the user's in vivo medical data and in vitro medical data.

[0006] The processor end of the medical platform is used to determine whether the user is an initial user based on the user's own information. When the user is an initial user, the user's initial disease information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database. When the user is a historical user, the user's historical physical condition information and the user's corresponding target doctor information are determined based on the user's own information, and the user's initial disease information is obtained based on the first medical data and the user's historical physical condition information. In response to the initial disease information, an instruction to obtain the user's second medical data is issued to the user acquisition end.

[0007] The user acquisition end is also used to obtain the user's tongue image information, facial expression image information and fundus image information taken by the medical platform, and the user's living habit information and current medication information input by the user according to the second medical data instruction sent by the processor end of the medical platform.

[0008] The processor end of the medical platform is also used to determine the user's final symptom information based on the initial symptom information and the second medical data, determine the user's treatment plan information based on the user's final symptom information, send the user's final symptom information and the user's treatment plan information to the user receiving end, and predict the user's symptom trend information based on the user's final symptom information, the user's treatment plan information and the user's historical physical condition information.

[0009] The user receiving end is used to receive the user's final symptom information and the user's treatment plan information.

[0010] Optionally, based on the correlation between the user's first medical data and the medical data of other users in the database, the user's initial disease information is obtained, including: determining the user's body part information based on the user's in vitro medical data; based on the user's body part information, querying the database for body part related data of other users that are most similar to the user's body part information; recording the body part related data of other users in the database that are most similar to the user's body part information as first data; based on the user's in vivo medical data, querying the in vivo data of other users in the first data that are ranked in the top three in similarity to the user's in vivo data, to obtain the user's initial disease information.

[0011] Optionally, based on the user's own information, the user's historical physical condition information and the target doctor information corresponding to the user are determined, including: based on the user's own information, querying the user's historical medical data, historical disease information, historical prescription information and historical recovery degree information and the user's corresponding doctor information in the database, wherein the historical recovery information is the user's recovery information after each treatment in the historical treatment process; based on the user's historical disease information and the user's historical recovery degree information, obtaining the user's historical physical condition information; establishing a curve graph between the user's historical recovery degree information and the treatment time, and calculating the area corresponding to the historical curve to obtain multiple treatment coefficients; sorting the multiple treatment coefficients, and determining the doctor information of the treatment time with the highest treatment coefficient as the user's target doctor information.

[0012] Optionally, the user's initial disease information is obtained based on the first medical data and the user's historical physical condition information, including: determining the location information of the user's disease based on the in vitro medical data in the first medical data information; determining the user's disease information based on the user's disease location information and the user's in vivo medical data; and obtaining the user's initial disease information based on the user's disease information and the user's historical physical condition information.

[0013] Optionally, determining the final symptom information of the user based on the initial symptom information and the second medical data includes: modifying or further determining the initial symptom information through the second medical data to obtain the final symptom information of the user.

[0014] Optionally, based on the final symptom information, the user's treatment plan information and the user's historical physical condition information, the user's symptom trend information is predicted, including: obtaining first trend information of the user's symptom based on the final symptom information and the user's treatment plan information; and determining the final trend information of the user's symptom based on the user's final symptom information and the first trend information of the user's symptom.

[0015] Optionally, after determining the user's historical physical condition information and the target doctor information corresponding to the user based on the user's own information, it also includes: based on the first medical data and the user's historical physical condition information, the user's initial disease information is not confirmed, the user's disease information is determined to be miscellaneous disease information, and a warning message is sent to the doctor end of the medical platform.

[0016] In an embodiment of the present invention, a user acquisition terminal is used for a user to input his / her own information and first medical data of the user obtained by a medical platform, wherein the self-information is the user's ID card information, and the first medical data is the user's internal medical data and external medical data; a processor terminal of the medical platform is used to determine whether the user is an initial user based on the user's own information, and when the user is an initial user, the user's initial symptom information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database; when the user is a historical user, the user's historical physical condition information and the target doctor information corresponding to the user are determined based on the user's own information, and the user's initial symptom information is obtained based on the first medical data and the user's historical physical condition information, and in response to the initial symptom information, an instruction to obtain the user's second medical data is issued to the user acquisition terminal; the user acquisition terminal is also used to determine whether the user is an initial user based on the processor terminal of the medical platform. The second medical data instruction sent obtains the user's tongue image information, facial expression image information and fundus image information taken by the medical platform, and the living habit information and current medication information input by the user; the processor end of the medical platform is also used to determine the user's final symptom information based on the initial symptom information and the second medical data, determine the user's treatment plan information based on the user's final symptom information, send the user's final symptom information and the user's treatment plan information to the user receiving end, and predict the user's symptom trend information based on the user's final symptom information, the user's treatment plan information and the user's historical physical condition information; the user receiving end is used to receive the user's final symptom information and the user's treatment plan information, which solves the current technical problems of patients' difficulty in seeing a doctor, patients' lack of previous medical records, and low disease cure rate, and achieves the technical effect of making it easy for patients to see a doctor and automatically archiving patients' previous medical records, thereby improving the disease cure rate.

[0017] Advantages of the present invention: Compared with the existing technology, the present invention determines the patient's disease location information based on the user's in vitro medical data, and determines the patient's symptom information based on the user's tongue image information, facial expression image information and fundus image information taken by the medical platform, and the living habit information and current medication information input by the user. Based on the patient's symptom information, treatment plan and the patient's historical physical condition, the present invention predicts the patient's symptom trend. Through the three-step method, the patient's condition is further understood and the patient's symptom cure rate is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 This is a structural block diagram of an intelligent decision-making auxiliary diagnosis and treatment platform according to an embodiment of the present invention; Figure 2 It is a method flow chart of an intelligent decision-making auxiliary diagnosis and treatment platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only embodiments of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0021] Example 1 According to an embodiment of the present invention, an intelligent decision-making auxiliary diagnosis and treatment platform is provided. Figure 1 is a structural block diagram of an intelligent decision-making auxiliary diagnosis and treatment platform according to an embodiment of the present invention. Figure 1As shown, an intelligent decision-making auxiliary diagnosis and treatment platform may include: a user acquisition end, a processor end of a medical platform, and a user receiving end.

[0022] The user acquisition end is used for the user to input his own information and the user's first medical data obtained by the medical platform, wherein the self-information is the user's ID card information, and the first medical data is the user's in vivo medical data and in vitro medical data.

[0023] In this embodiment, the user inputs his own information through the user input terminal of the medical platform interface, and the pulse system of the medical platform obtains the user's pulse signal. The user's pulse signal is the in vivo medical data. The in vivo medical data can also be the experimental test data of the user's body, such as blood, urine, tissue samples, or medical imaging data or the user's self-reported symptoms, etc., which are not specifically limited here, only for example. The in vitro medical data is which part of the user's body is painful or the user's current physical symptoms, such as the degree of tinnitus, the degree of headache, etc., which are not specifically limited here, only for example. Among them, the user's identity information refers to the user's ID number information.

[0024] The processor end of the medical platform is used to determine whether the user is an initial user based on the user's own information. When the user is an initial user, the user's initial disease information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database. When the user is a historical user, the user's historical physical condition information and the user's corresponding target doctor information are determined based on the user's own information, and the user's initial disease information is obtained based on the first medical data and the user's historical physical condition information. In response to the initial disease information, an instruction to obtain the user's second medical data is issued to the user acquisition end.

[0025] In this embodiment, the processor of the medical platform determines whether the user is an initial user by screening the identity card information input by the user. When the user is an initial user, the user's initial disease information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database. For example, the correlation between the user's first medical data and the medical data of the 890th user in the database reaches 96%. When it is determined that the user is a historical user based on the user's own identity information, the user's historical physical condition information and the target doctor corresponding to the user are obtained based on the user's own information. The user's initial disease information is obtained based on the first medical data and the user's historical physical condition information. After obtaining the user's initial disease information, an instruction to obtain the user's second medical data is sent to the user acquisition terminal.

[0026] The user acquisition end is also used to obtain the user's tongue image information, facial expression image information and fundus image information taken by the medical platform, and the user's living habit information and current medication information input by the user according to the second medical data instruction sent by the processor end of the medical platform.

[0027] The user acquisition end obtains the user's tongue image information, facial expression image information and fundus image information according to the second medical data instruction sent by the processor end of the medical platform and the camera of the medical platform. At the user input end, the user inputs his or her living habit information and current medication information. For example, if the living schedule is irregular, the current medication information may be the current medicine order information.

[0028] The processor end of the medical platform is also used to determine the user's final symptom information based on the initial symptom information and the second medical data, determine the user's treatment plan information based on the user's final symptom information, send the user's final symptom information and the user's treatment plan information to the user receiving end, and predict the user's symptom trend information based on the user's final symptom information, the user's treatment plan information and the user's historical physical condition information.

[0029] The processor end of the medical platform combines the initial symptom information with the second medical data to obtain the final symptom information, obtains the user's treatment plan information based on the user's final symptom information, sends the user's final symptom information and the user's treatment plan information to the user receiving end, and further predicts the user's symptom trend information based on the final symptom information, the user's treatment plan information and the user's historical physical condition information.

[0030] The user receiving end is used to receive the user's final symptom information and the user's treatment plan information.

[0031] Optionally, based on the correlation between the user's first medical data and the medical data of other users in the database, the user's initial disease information is obtained, including: determining the user's body part information based on the user's in vitro medical data; based on the user's body part information, querying the database for body part related data of other users that are most similar to the user's body part information; recording the body part related data of other users in the database that are most similar to the user's body part information as first data; based on the user's in vivo medical data, querying the in vivo data of other users in the first data that are ranked in the top three in similarity to the user's in vivo data, to obtain the user's initial disease information.

[0032] In this embodiment, when the user's in vitro medical data is physical symptom information input by the user himself, the user has a swollen throat, a lot of sputum, asthma, and repeated coughing, and the user's body part information is determined to be bronchus. Based on the user's body part being bronchus, the database is queried for relevant data on the bronchi of other users whose body parts are most similar to the user's body parts, and the body part relevant data of other users in the database with the highest similarity to the bronchial part is recorded as the first data. Based on the user's in vivo medical data, for example, severe cough, yellow sputum, and normal other in vivo body data, based on the user's in vivo data, the user's in vivo data is calculated for similarity with the in vivo data in the first data to obtain the in vivo data of the top three other users ranked in similarity. Based on the in vivo data of the top three other users ranked in similarity, it is preliminarily determined that the user's initial symptom information is in the cough range.

[0033] Optionally, based on the user's own information, the user's historical physical condition information and the target doctor information corresponding to the user are determined, including: based on the user's own information, querying the user's historical medical data, historical disease information, historical prescription information and historical recovery degree information and the user's corresponding doctor information in the database, wherein the historical recovery information is the user's recovery information after each treatment in the historical treatment process; based on the user's historical disease information and the user's historical recovery degree information, obtaining the user's historical physical condition information; establishing a curve graph between the user's historical recovery degree information and the treatment time, and calculating the area corresponding to the historical curve to obtain multiple treatment coefficients; sorting the multiple treatment coefficients, and determining the doctor information of the treatment time with the highest treatment coefficient as the user's target doctor information.

[0034] For example, based on the user's own information, the user's historical medical data queried in the database is cough and sputum 5 years ago, the historical disease information is the user cough, the historical prescription information is Yifei Huatan Decoction plus 9g of Atractylodes, 10g each of Cinnamon, Terminalia chebula, Aster, and Coltsfoot, 15g of Psoralea corylifolia, 6 doses, 1 dose / d, decocted in 400ml of water, divided into morning and evening, the historical recovery information is the recovery information after taking each dose of medicine, and the historical recovery information is 60%, 70%, 73%, 75%, and 80% respectively. The second diagnosis is underway, and the symptoms of the second diagnosis are: cough, sputum, and asthma are significantly alleviated compared to before, but there is still fatigue, aversion to wind and cold, good appetite and sleep, and regular bowel movements. The tongue is pale and dark with a greasy white coating, and the pulse is deep and fine. The second diagnosis prescription is Yifei Huatan Decoction plus Atractylodes 9g, Cinnamon Bark, Terminalia Terminalia 10g each, Asarum, Dry Ginger 3g each, Psoralea corylifolia 15g, 6 doses, 1 dose / d, decocted in 400ml of water, and the historical recovery information is 80%, 86%, 90%, 95%, and 100% respectively; or the historical prescription is other prescriptions, 5 sets of medicine are taken, it is the prescription prescribed by Doctor Huang A, and the historical recovery information is 30%, 35%, 40%, 45%, and 60% respectively. After the user conducts a review, other prescriptions are prescribed, 5 sets of medicine are taken, it is the prescription prescribed by Doctor Ding A, and the historical recovery information is 100% respectively. Forty percent, forty-five percent, fifty percent, sixty percent, and sixty percent. Based on the historical disease information and the user's historical recovery information, the user's physical condition information is obtained. The cough is a stubborn disease and needs to be treated with medicine. The number of doses of medicine and the treatment time are matched. The treatment time for one dose of medicine is one day. The treatment time is used as the horizontal axis, and the historical recovery degree corresponding to the treatment time is used as the vertical axis. Points are plotted and a curve graph is drawn. The curve graph is integrated to obtain multiple treatment coefficients. The multiple treatment coefficients are sorted, and the doctor information with the treatment time with the highest treatment coefficient is determined as the user's target doctor information. For example, the target doctor is Dr. Huang A.

[0035] Optionally, the user's initial disease information is obtained based on the first medical data and the user's historical physical condition information, including: determining the location information of the user's disease based on the in vitro medical data in the first medical data information; determining the user's disease information based on the user's disease location information and the user's in vivo medical data; and obtaining the user's initial disease information based on the user's disease information and the user's historical physical condition information.

[0036] For example, when the in vitro medical data of the first medical data information is chest tightness, shortness of breath, cough, white sputum in the morning, loss of appetite, fatigue, and tiredness, it is determined that the location of the user's disease is the lung, and based on the user's disease location information and the user's in vivo medical data and routine blood test data, the user's disease information is obtained as lung and spleen qi deficiency, and internal obstruction of phlegm and dampness. The historical physical condition is asthma and cough for more than 10 years and the disease information is lung and spleen qi deficiency, and internal obstruction of phlegm and dampness. The user's initial disease information is lung distension and cough.

[0037] Optionally, determining the final symptom information of the user based on the initial symptom information and the second medical data includes: modifying or further determining the initial symptom information through the second medical data to obtain the final symptom information of the user.

[0038] For example, when the second medical data of the user is a pale red tongue with a greasy white coating, it is further determined that the final disease information of the user is lung distension and cough.

[0039] Optionally, based on the final symptom information, the user's treatment plan information and the user's historical physical condition information, the user's symptom trend information is predicted, including: obtaining first trend information of the user's symptom based on the final symptom information and the user's treatment plan information; and determining the final trend information of the user's symptom based on the user's final symptom information and the first trend information of the user's symptom.

[0040] For example, the user's final symptom information is lung distension and cough, and the user's treatment plan information is Yifei Huatan Decoction plus 10g of raw gypsum, 30g of hemp seed, and 15g of stir-fried rhubarb. 6 doses, one dose per day, 400ml of water decoction, taken in the morning and evening, the first trend information of the user's symptom is that the lung distension and cough are greatly alleviated. According to the user's final symptom information and the first trend information of the user's symptom, the final trend information of the user's symptom is that the lung distension and cough are cured.

[0041] Optionally, after determining the user's historical physical condition information and the target doctor information corresponding to the user based on the user's own information, it also includes: based on the first medical data and the user's historical physical condition information, the user's initial disease information is not confirmed, the user's disease information is determined to be miscellaneous disease information, and a warning message is sent to the doctor end of the medical platform.

[0042] In this embodiment, if the user's initial disease information cannot be determined based on the first medical data and the user's historical physical condition information, the user's disease information is determined to be miscellaneous disease information, and a warning message is sent to the doctor side of the medical platform, and the doctor diagnoses and treats the user.

[0043] In this embodiment, the user acquisition end is used for the user to input his own information and the first medical data of the user obtained by the medical platform, wherein the own information is the user's ID card information, and the first medical data is the user's internal medical data and external medical data; the processor end of the medical platform is used to determine whether the user is an initial user based on the user's own information, and when the user is an initial user, the user's initial disease information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database; when the user is a historical user, the user's historical physical condition information and the target doctor information corresponding to the user are determined based on the user's own information, and the user's initial disease information is obtained based on the first medical data and the user's historical physical condition information. In response to the initial disease information, an instruction to obtain the user's second medical data is issued to the user acquisition end; The user acquisition end is also used to obtain the user's tongue image information, facial expression image information and fundus image information taken by the medical platform, and the user's living habit information and current medication information input by the medical platform according to the second medical data instruction sent by the processor end of the medical platform; the processor end of the medical platform is also used to determine the user's final symptom information based on the initial symptom information and the second medical data, determine the user's treatment plan information based on the user's final symptom information, send the user's final symptom information and the user's treatment plan information to the user receiving end, and predict the user's symptom trend information based on the user's final symptom information, the user treatment plan information and the user's historical physical condition information. The user receiving end is used to receive the user's final symptom information and the user's treatment plan information, which solves the current technical problems of patients' difficulty in seeing a doctor, patients' lack of previous medical records, and low disease cure rate, and achieves the technical effect of making it easy for patients to see a doctor and automatically archiving patients' previous medical records, thereby improving the disease cure rate.

[0044] Example 2 According to an embodiment of the present invention, a method for an intelligent decision-making assisted diagnosis and treatment platform is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system comprising at least one set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0045] Figure 2 is a method flow chart of an intelligent decision-making auxiliary diagnosis and treatment platform according to an embodiment of the present invention. Figure 2 As shown, the method may include the following steps: Step S201, obtaining the user's own information and first medical data input by the user, wherein the self-information is the user's ID card information, and the first medical data is the user's in-vivo medical data and in-vitro medical data.

[0046] In the technical solution provided in the above step S201 of the present invention, the user inputs his own information through the user input terminal of the medical platform interface, and the pulse system of the medical platform obtains the user's pulse signal, and the user's pulse signal is the in vivo medical data. The in vivo medical data can also be the experimental test data of the user's body, such as blood, urine, tissue samples, or medical imaging data or the user's self-reported symptoms, etc., which are not specifically limited here, only for example. The in vitro medical data is which part of the user's body is painful or the user's current physical symptoms, such as the degree of tinnitus, the degree of headache, etc., which are not specifically limited here, only for example. Among them, the user's identity information refers to the user's ID number information.

[0047] Step S202, based on the user's own information, determine whether the user is an initial user. When the user is an initial user, based on the correlation between the user's first medical data and the medical data of other users in the database, obtain the user's initial disease information. When the user is a historical user, based on the user's own information, determine the user's historical physical condition information and the user's corresponding target doctor information, obtain the user's initial disease information based on the first medical data and the user's historical physical condition information, and in response to the initial disease information, issue an instruction to obtain the user's second medical data.

[0048] In the technical solution provided in the above step S202 of the present invention, it is determined whether the user is an initial user based on the user's ID card information. When the user is an initial user, the user's initial disease information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database, for example, the correlation between the user's first medical data and the medical data of the 890th-ranked user in the database reaches 96%. When it is determined that the user is a historical user based on the user's own identity information, the user's historical physical condition information and the target doctor corresponding to the user are obtained based on the user's own information. The user's initial disease information is obtained based on the first medical data and the user's historical physical condition information. After obtaining the user's initial disease information, an instruction to obtain the user's second medical data is issued to the user acquisition end.

[0049] Step S203, obtaining the user's second medical data, wherein the second medical data includes at least one of the following: the user's tongue image information, facial expression image information and fundus image information, the user's living habit information and current medication information.

[0050] In the technical solution provided in the above step S203 of the present invention, the camera of the medical platform captures the user's tongue image information, facial expression image information and fundus image information, and the user inputs his or her own living habit information and current medication information.

[0051] Step S204, based on the initial symptom information and the second medical data, determine the user's final symptom information, based on the user's final symptom information, determine the user's treatment plan information, send the user's final symptom information and the user's treatment plan information to the user receiving end, and based on the user's final symptom information, the user's treatment plan information and the user's historical physical condition information, predict the user's symptom trend information.

[0052] In the technical solution provided in the above step S204 of the present invention, the initial symptom information is combined with the second medical data to obtain the final symptom information, and the user's treatment plan information is obtained based on the user's final symptom information. The user's final symptom information and the user's treatment plan information are sent to the user receiving end, and the user's symptom trend information is further predicted based on the final symptom information, the user's treatment plan information and the user's historical physical condition information.

[0053] In an embodiment of the present invention, the user's inputted self-information and first medical data are obtained, wherein the self-information is the user's ID card information, and the first medical data is the user's internal medical data and external medical data; based on the user's self-information, whether the user is an initial user is determined; when the user is an initial user, the user's initial symptom information is obtained based on the correlation between the user's first medical data and the medical data of other users in the database; when the user is a historical user, the user's historical physical condition information and the user's corresponding target doctor information are determined based on the user's self-information; the user's initial symptom information is obtained based on the first medical data and the user's historical physical condition information; in response to the initial symptom information, an instruction to obtain the user's second medical data is issued; the user's second medical The second medical data includes at least one of the following: the user's tongue image information, facial expression image information and fundus image information, the user's living habit information and current medication information; based on the initial symptom information and the second medical data, the user's final symptom information is determined, based on the user's final symptom information, the user's treatment plan information is determined, the user's final symptom information and the user's treatment plan information are sent to the user receiving end, based on the user's final symptom information, the user's treatment plan information and the user's historical physical condition information, the user's symptom trend information is predicted, which solves the current technical problems of patients' difficulty in seeing a doctor, patients' lack of previous medical records, and low disease cure rate, and achieves the technical effect of making it easy for patients to see a doctor and automatically archiving patients' previous medical records to improve disease cure rate.

[0054] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0055] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0056] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0057] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0058] In addition, each functional unit in each embodiment of the present invention may be integrated into a first processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0059] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0060] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An intelligent decision-making auxiliary diagnosis and treatment platform, characterized in that: include: A user acquisition terminal, used for the user to input his / her own information and the first medical data of the user obtained by the medical platform, wherein the personal information is the ID card information of the user, and the first medical data is the in vivo medical data and in vitro medical data of the user; The processor end of the medical platform is used to determine whether the user is an initial user based on the user's own information, and when the user is an initial user, obtain the user's initial disease information based on the correlation between the user's first medical data and the medical data of other users in the database; when the user is a historical user, determine the user's historical physical condition information and the target doctor information corresponding to the user based on the user's own information, obtain the user's initial disease information based on the first medical data and the user's historical physical condition information, and issue an instruction to obtain the user's second medical data to the user acquisition end in response to the initial disease information; The user acquisition end is further used to acquire the tongue image information, facial expression image information and fundus image information of the user photographed by the medical platform, and the living habit information and current medication information input by the user according to the second medical data instruction sent by the processor end of the medical platform; The processor end of the medical platform is further used to determine the final symptom information of the user based on the initial symptom information and the second medical data, determine the treatment plan information of the user based on the final symptom information of the user, send the final symptom information of the user and the treatment plan information of the user to the user receiving end, and predict the symptom trend information of the user based on the final symptom information of the user, the treatment plan information of the user and the historical physical condition information of the user; The user receiving end is used to receive the final symptom information of the user and the treatment plan information of the user.

2. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1 is characterized in that: The obtaining of the initial disease information of the user based on the correlation between the first medical data of the user and the medical data of other users in the database includes: Determining body part information of the user according to the in vitro medical data of the user; Based on the body part information of the user, query the database for body part related data of other users having the highest similarity to the body part information of the user; Recording the body part related data of other users in the database that have the highest similarity to the body part information of the user as first data; According to the in vivo medical data of the user, the in vivo data of other users whose similarity to the in vivo data of the user is ranked top three in the first data are queried to obtain the initial disease information of the user.

3. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1 is characterized in that: The determining, based on the user's own information, the user's historical physical condition information and the target doctor information corresponding to the user includes: Based on the user's own information, query the database for the user's historical medical data, historical disease information, historical prescription information, historical recovery degree information, and the user's corresponding doctor information, wherein the historical recovery information is the user's recovery information after each treatment in the historical treatment process; Based on the historical disease information of the user and the historical recovery degree information of the user, obtaining the historical physical condition information of the user; Establishing a curve graph between the historical recovery degree information of the user and the treatment time, and calculating the area corresponding to the historical curve to obtain a plurality of treatment coefficients; The multiple treatment coefficients are sorted, and the doctor information of the treatment time with the highest treatment coefficient is determined as the target doctor information of the user.

4. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1 is characterized in that: The obtaining the initial disease information of the user based on the first medical data and the historical physical condition information of the user includes: Determining location information of the user's disease according to the in vitro medical data in the first medical data information; Determining the disease type information of the user based on the location information of the user's disease and the user's in vivo medical data; Based on the disease information of the user and the historical physical condition information of the user, the initial disease information of the user is obtained.

5. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1 is characterized in that: The determining, based on the initial symptom information and the second medical data, final symptom information of the user comprises: The initial symptom information is modified or further determined through the second medical data to obtain the final symptom information of the user.

6. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1, characterized in that: The predicting of the user's symptom trend information based on the final symptom information, the user's treatment plan information and the user's historical physical condition information includes: Based on the final symptom information and the treatment plan information of the user, obtaining first trend information of the symptom of the user; Based on the final symptom information of the user and the first trend information of the symptom of the user, final trend information of the symptom of the user is determined.

7. The intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1 is characterized in that: After determining the historical physical condition information of the user and the target doctor information corresponding to the user based on the user's own information, the method further includes: Based on the first medical data and the historical physical condition information of the user, the initial symptom information of the user is not confirmed, the symptom information of the user is determined to be miscellaneous symptom information, and a warning message is sent to the doctor end of the medical platform.

8. The method of an intelligent decision-making auxiliary diagnosis and treatment platform according to claim 1, characterized in that: include: Acquire the user's own information and first medical data input by the user, wherein the self-information is the user's ID card information, and the first medical data is the user's in-vivo medical data and in-vitro medical data; Based on the user's own information, determine whether the user is an initial user; when the user is an initial user, obtain the user's initial disease information based on the correlation between the user's first medical data and the medical data of other users in the database; when the user is a historical user, determine the user's historical physical condition information and the target doctor information corresponding to the user based on the user's own information, obtain the user's initial disease information based on the first medical data and the user's historical physical condition information, and issue an instruction to obtain the user's second medical data in response to the initial disease information; Acquiring second medical data of the user, wherein the second medical data includes at least one of the following: tongue image information, facial expression image information and fundus image information of the user, and living habit information and current medication information of the user; Based on the initial symptom information and the second medical data, the final symptom information of the user is determined; based on the final symptom information of the user, the treatment plan information of the user is determined; the final symptom information of the user and the treatment plan information of the user are sent to the user receiving end; based on the final symptom information of the user, the treatment plan information of the user and the historical physical condition information of the user, the symptom trend information of the user is predicted.

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