Digital doctor education and promotion model building system and solving method thereof

Abstract

The invention discloses a digital doctor education and promotion model establishing system and a solving method thereof, and belongs to the technical field of digital doctors, and the digital doctor education and promotion model establishing system comprises a doctor-side digital education promotion model and a patient-side digital education promotion model. According to the method, the digital image is created based on the AI digital human technology, the personalized MDV multi-modal database is established for each doctor through the AIGC service tool, the personal digital doctor image can be quickly generated and adjusted, the construction process is simplified, and therefore when the digital doctor is popularized, the operation process is simplified, the personal digital doctor image establishment threshold is lowered, and the digital doctor experience is improved. The system is beneficial to popularization and promotion when oriented to a doctor side, assists a patient in saving communication and way asking time in a diagnosis process, simplifies the diagnosis process and knows related science popularization information processed in each link, is beneficial to transparency of the diagnosis process and reduces understanding difficulty of an examination process, and is beneficial to popularization and promotion when oriented to a patient side.

Description

Technical Field

[0001] The present invention relates to the technical field of digital doctors, and in particular to a digital doctor education and promotion model establishment system and a solution thereof. Background Art

[0002] With the continuous improvement of the level of social informatization, in the medical field, people have created AI digital doctor images based on digital human technology, and the doctor image appears to provide patients with personalized popular science content covering the entire process before, during and after diagnosis. This can improve the efficiency of doctors' analysis of patients' conditions, improve the convenience of medical services, and achieve the purpose of digital medicine.

[0003] At present, the penetration rate of digital doctors in China is seriously low, resulting in that at the patient level, most patients still need to go through the traditional medical treatment model of registration, queuing and diagnosis, wasting a lot of time and not being able to get timely medical diagnosis and condition analysis. At the doctor level, most doctors still need to tediously review case records and understand the patient's basic condition through verbal communication. They cannot conduct targeted condition analysis at the time of diagnosis, resulting in a waste of medical resources and many problems such as limited consultation quotas and patients not being able to get a number even if they have to wait in long lines. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that the current penetration rate of digital doctors is seriously low, causing patients to waste too much time in the traditional medical process from registration, queuing to diagnosis, and doctors need to understand the basic condition of each patient from the beginning before making a diagnosis, resulting in a shortage of medical resources and the inability to diagnose the patient's condition in time. A digital doctor education and promotion model establishment system and its solution are proposed.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A digital doctor education and promotion model establishment system is respectively oriented to doctors and patients, including a doctor-side digital education promotion model and a patient-side digital education promotion model. The doctor-side digital education promotion model consists of a doctor learning module and a doctor-side promotion module, providing a learning platform for doctors and promoting the establishment of digital doctors. The patient-side digital education promotion model consists of a patient teaching module and a patient-side promotion module, providing patients with teaching and promoting the practice of digital doctors.

[0007] Preferably, the doctor learning module is provided with a digital doctor establishment submodule and a digital doctor personalized learning submodule, which are used to form a unique digital doctor image for each doctor, and the doctor-side promotion module is provided with an offline diagnosis assistance submodule and an online diagnosis assistance submodule, which are used to promote and introduce the diagnosis assistance function of the digital doctor for the doctor-side;

[0008] The digital doctor establishment submodule adopts AI digital human technology to create a digital image, and through the AIGC service tool, establishes a personalized MDV multimodal database for each doctor to assist learning and generate digital doctor-related videos.

[0009] Preferably, the patient teaching module is provided with a medical knowledge teaching submodule and a diagnosis interaction teaching submodule, and the patient-side promotion module is provided with an online diagnosis record submodule for promoting and introducing the diagnosis assistance function of the digital doctor for the patient-side.

[0010] A promotion solution for a digital doctor education and promotion model establishment system includes a doctor-side digital education promotion solution and a patient-side digital education promotion solution. The doctor-side digital education promotion solution includes the following processing steps:

[0011] S1: Promotion of digital image: Simplifying the construction process through digital human, promoting and establishing the digital doctor image to doctors and pharmaceutical and medical device companies;

[0012] S2: Digital teaching promotion, through personal learning assistance and digital doctor learning assistance process, promote the convenient learning method of doctor-side digital education promotion model to doctors;

[0013] S3: Diagnosis-assisted promotion, through the interactive communication between digital doctors and patients online to assist the offline diagnosis process and promote the digital doctor operation model to doctors;

[0014] The patient-side digital education promotion solution includes the following processing steps:

[0015] Step 1: Promote digital science, and let digital doctors professionally interpret disease-related knowledge to instill in patients the concept of digital doctors’ high professionalism;

[0016] Step 2: Simplify and promote diagnosis. Through online communication with digital doctors, patients can quickly see a doctor and obtain timely information related to diagnosis, such as popular science of relevant examination items, popular science of prescriptions and medical orders, and professional interpretation of reports, to promote the efficient practical application of digital doctors to patients.

[0017] Preferably, in step S1, the image, video and voice information of the doctor are input into the personal AI digital human database by using the hyper-realistic AI digital human technology, and the image and voiceprint creation is completed by using the image learning and voice cloning technology;

[0018] In image learning, realistic character images are generated through deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. In voice cloning, speech recognition technology, speech synthesis technology, machine learning technology, and machine hearing technology are used to simulate real-person original voices with high fidelity.

[0019] Preferably, in step S2, the method for building a database of doctors through the doctor-side digital education promotion model is:

[0020] S21: Establish an initial database by injecting the knowledge and experience of medical experts in the field as initial audio and video into the total MDV multimodal database to form an initial database of digital doctor image knowledge data;

[0021] S22: Establish a personal database, and use AIGC service tools to assist doctors in learning medical professional knowledge by using text, pictures, and videos. Based on the initial database of digital doctor image knowledge data, adjust the personal MDV multimodal database to adjust the professional knowledge of the personal digital doctor image to form a personal personalized MDV multimodal database.

[0022] Preferably, in step S3, the doctor-side promotion module assists the doctor in making a diagnosis according to the patient's diagnosis and treatment process:

[0023] S31: Pre-diagnosis understanding: the digital doctor records the patient's basic condition in advance through questions and answers and patient text input;

[0024] S32: Improve efficiency during diagnosis. By recording the basic condition of the patient, doctors can understand the patient's condition, save consultation time, and speed up the medical diagnosis. Digital doctors can also educate and popularize scientific examinations, saving time on explaining examination items.

[0025] S33: Post-diagnosis medical advice combines the medical diagnosis results with the patient's special instructions for the use of medicines, and forms a digital medical advice through the corresponding content in the digital doctor, saving time for medical advice explanation.

[0026] In step 2, the patient-side digital education promotion model assists patients in diagnosis in the following steps according to the patient's diagnosis and treatment process:

[0027] Pre-diagnosis knowledge popularization: Before seeing a doctor, patients can communicate with the digital doctor online in the form of questions and answers by inputting text, audio and video information. The digital doctor can also popularize and record the patient's medical problems to help the patient understand the relevant knowledge of the disease.

[0028] Accompanying during consultation: When seeing a doctor, patients can communicate with digital doctors to obtain detailed information about offline hospitals, such as navigation to doctors' clinics and consultation queue information, as well as scientific information about examination items. When the digital doctor determines that the patient meets the doctor's diagnostic criteria, the patient can make an appointment, thus solving the problem of wasted and mismatched medical resources, such as patients not being able to make an appointment or making the wrong appointment.

[0029] Post-diagnosis interpretation: After the consultation, patients can communicate with digital doctors to obtain digital medical advice and prescription information, as well as report interpretations, so that they can know and understand their own medical diagnosis results.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. Create digital images based on AI digital human technology. Through the AIGC service tool, a personalized MDV multimodal database is established for each doctor. It can quickly generate and adjust personal digital doctor images and simplify the construction process. Therefore, when promoting and popularizing digital doctors, it can be easier for doctors to understand through the simplified process of establishing specific models. The simplified operation process lowers the threshold for establishing personal digital doctor images, which is conducive to popularization and promotion when facing doctors.

[0032] 2. By establishing a personal digital doctor image, doctors can be assisted in the process of diagnosing patients, saving time on consultations, related examination items, medical orders and prescriptions, thereby improving the doctor's diagnostic efficiency and saving medical and patient resources. It is also convenient for doctors to increase the popularity of digital doctors after understanding the convenience of digital doctor applications.

[0033] 3. By establishing a personal digital doctor image, patients can save time on communication and asking for directions during the diagnosis process, simplify the diagnosis process and understand the relevant popular science information processed in each link, which is conducive to the transparency of the diagnosis process and reduces the difficulty of understanding the examination process, which is conducive to popularization and promotion when facing the patient side. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A system block diagram of a digital doctor education and promotion model establishment system proposed by the present invention;

[0035] Figure 2 A flowchart of a doctor-side digital education and promotion solution for establishing a system promotion solution for a digital doctor education and promotion model proposed by the present invention;

[0036] Figure 3 A flowchart of a patient-side digital education and promotion solution for establishing a system promotion solution for a digital doctor education and promotion model proposed in the present invention. DETAILED DESCRIPTION

[0037] The technical solutions 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 part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0038] Example, see Figures 1 to 3A digital doctor education and promotion model establishment system is designed for doctors and patients respectively, including a doctor-side digital education promotion model and a patient-side digital education promotion model. The doctor-side digital education promotion model consists of a doctor learning module and a doctor-side promotion module, providing a learning platform for doctors and promoting the establishment of digital doctors. The patient-side digital education promotion model consists of a patient teaching module and a patient-side promotion module, providing patients with teaching and promotion of digital doctors.

[0039] It should be noted that: education for doctors is divided into personal education and the education process of adjusting their personal digital doctor image; education for patients is to assist patients in understanding their condition and the overall diagnosis process through popular science of digital doctors; and promotion for doctors and patients is carried out through specific establishment steps within the digital education promotion model for doctors and the digital education promotion model for patients, respectively.

[0040] Furthermore, the doctor learning module is provided with a digital doctor establishment submodule and a digital doctor personalized learning submodule, which are used to form a unique digital doctor image for each doctor, and the doctor-side promotion module is provided with an offline diagnosis assistance submodule and an online diagnosis assistance submodule, which are used to promote and introduce the diagnosis assistance function of the digital doctor for the doctor-side;

[0041] It should be noted that the digital doctor establishment submodule uses AI digital human technology to create a digital image. Through the AIGC service tool, a personalized MDV multimodal database is established for each doctor to assist in learning and generate digital doctor-related videos. The digital doctor personalized learning submodule adjusts the interpretation of personal digital doctor professional knowledge by learning professional knowledge and the professional knowledge and experience of medical experts.

[0042] Furthermore, the patient teaching module is provided with a medical knowledge teaching sub-module and a diagnosis interaction teaching sub-module, and the patient-side promotion module is provided with an online diagnosis record sub-module, which are used to promote and introduce the diagnosis assistance function of the digital doctor for the patient side.

[0043] It should be noted that the medical knowledge teaching sub-module is often set up before and after the patient's diagnosis. The patient's pre-diagnosis condition-related knowledge and post-diagnosis medical instructions and reports are interpreted to the patient in the form of popular science. The diagnostic interactive teaching sub-module is to explain the patient's clinic-related information such as hospital navigation and examination item content to assist him in his medical treatment.

[0044] like Figure 2 and Figure 3 As shown, a promotion solution for establishing a digital doctor education and promotion model system includes a doctor-side digital education promotion solution and a patient-side digital education promotion solution. The doctor-side digital education promotion solution includes the following processing steps:

[0045] S1: Promotion of digital image: Simplifying the construction process through digital human, promoting and establishing the digital doctor image to doctors and pharmaceutical and medical device companies;

[0046] S2: Digital teaching promotion, through personal learning assistance and digital doctor learning assistance process, promote the convenient learning method of doctor-side digital education promotion model to doctors;

[0047] S3: Promotion of diagnosis assistance, through the interactive communication between digital doctors and patients online to assist the offline diagnosis process and promote the digital doctor operation model to doctors.

[0048] It should be noted that: in step S1, the doctor's image, video information and sound information are input into the personal AI digital human database using hyper-realistic AI digital human technology, and the image and voiceprint creation is completed using image learning and sound cloning technology;

[0049] In image learning, realistic character images are generated through deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. In voice cloning, speech recognition technology, speech synthesis technology, machine learning technology, and machine hearing technology are used to simulate real-person original voices with high fidelity.

[0050] Based on the above, in step S2, the method for building a database for doctors through the doctor-side digital education promotion model is:

[0051] S21: Establish an initial database by injecting the knowledge and experience of medical experts in the field as initial audio and video into the total MDV multimodal database to form an initial database of digital doctor image knowledge data;

[0052] S22: Establish a personal database, and use AIGC service tools to assist doctors in learning medical professional knowledge by using text, pictures, and videos. Based on the initial database of digital doctor image knowledge data, adjust the personal MDV multimodal database to adjust the professional knowledge of the personal digital doctor image to form a personal personalized MDV multimodal database.

[0053] Based on the above, in step S3, the doctor-side promotion module assists the doctor in making the following steps according to the patient's diagnosis and treatment process:

[0054] S31: Pre-diagnosis understanding: the digital doctor records the patient's basic condition in advance through questions and answers and patient text input;

[0055] S32: Improve efficiency during diagnosis. By recording the basic condition of the patient, doctors can understand the patient's condition, save consultation time, and speed up the medical diagnosis. Digital doctors can also educate and popularize scientific examinations, saving time on explaining examination items.

[0056] S33: Post-diagnosis medical advice combines the medical diagnosis results with the patient's special instructions for the use of medicines, and forms a digital medical advice through the corresponding content in the digital doctor, saving time for medical advice explanation.

[0057] The patient-side digital education promotion solution includes the following processing steps:

[0058] Step 1: Promote digital science, and let digital doctors professionally interpret disease-related knowledge to instill in patients the concept of digital doctors’ high professionalism;

[0059] Step 2: Simplify and promote diagnosis. Through online communication with digital doctors, patients can quickly see a doctor and obtain timely information related to diagnosis, such as popular science of relevant examination items, popular science of prescriptions and medical orders, and professional interpretation of reports, to promote the efficient practical application of digital doctors to patients.

[0060] It should be noted that in step 2, the patient-side digital education promotion model assists patients in diagnosis in the following steps according to the patient's diagnosis and treatment process:

[0061] Pre-diagnosis knowledge popularization: Before seeing a doctor, patients can communicate with the digital doctor online in the form of questions and answers by inputting text, audio and video information. The digital doctor can also popularize and record the patient's medical problems to help the patient understand the relevant knowledge of the disease.

[0062] Accompanying during consultation: When seeing a doctor, patients can communicate with digital doctors to obtain detailed information about offline hospitals, such as navigation to doctors' clinics and consultation queue information, as well as scientific information about examination items. When the digital doctor determines that the patient meets the doctor's diagnostic criteria, the patient can make an appointment, thus solving the problem of wasted and mismatched medical resources, such as patients not being able to make an appointment or making the wrong appointment.

[0063] Post-diagnosis interpretation: After the consultation, patients can communicate with digital doctors to obtain digital medical advice and prescription information, as well as report interpretations, so that they can know and understand their own medical diagnosis results.

[0064] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A digital doctor education and promotion model establishment system, for doctors and patients respectively, characterized by: It includes a doctor-side digital education promotion model and a patient-side digital education promotion model. The doctor-side digital education promotion model consists of a doctor learning module and a doctor-side promotion module, which provide doctors with a learning platform and promote the establishment of digital doctors. The patient-side digital education promotion model consists of a patient teaching module and a patient-side promotion module, which provide patients with teaching and promote the practice of digital doctors.

2. A digital doctor education and promotion model building system according to claim 1, characterized in that: The doctor learning module is provided with a digital doctor establishment submodule and a digital doctor personalized learning submodule, which are used to form a unique digital doctor image for each doctor; the doctor end promotion module is provided with an offline diagnosis assistance submodule and an online diagnosis assistance submodule, which are used to promote and introduce the diagnosis assistance function of digital doctors for the doctor end; The digital doctor establishment submodule adopts AI digital human technology to create a digital image, and through the AIGC service tool, establishes a personalized MDV multimodal database for each doctor to assist learning and generate digital doctor-related videos.

3. A digital doctor education and promotion model building system according to claim 1, characterized in that: The patient teaching module is provided with a medical knowledge teaching submodule and a diagnosis interaction teaching submodule, and the patient-side promotion module is provided with an online diagnosis record submodule for promoting and introducing the diagnosis auxiliary function of the digital doctor for the patient side.

4. A promotion solution proposed by a digital doctor education and promotion model establishment system according to any one of claims 1 to 3, characterized in that: The invention comprises a doctor-side digital education promotion solution and a patient-side digital education promotion solution, wherein the doctor-side digital education promotion solution comprises the following processing steps: S1: Promotion of digital image: Simplifying the construction process through digital human, promoting and establishing the digital doctor image to doctors and pharmaceutical and medical device companies; S2: Digital teaching promotion, through personal learning assistance and digital doctor learning assistance process, promote the convenient learning method of doctor-side digital education promotion model to doctors; S3: Diagnosis-assisted promotion, through the interactive communication between digital doctors and patients online to assist the offline diagnosis process and promote the digital doctor operation model to doctors; The patient-side digital education promotion solution includes the following processing steps: Step 1: Promote digital science, and let digital doctors professionally interpret disease-related knowledge to instill in patients the concept of digital doctors’ high professionalism; Step 2: Simplify and promote diagnosis. Through online communication with digital doctors, patients can quickly see a doctor and obtain timely information related to diagnosis, such as popular science of relevant examination items, popular science of prescriptions and medical orders, and professional interpretation of reports, to promote the efficient practical application of digital doctors to patients.

5. The promotion solution of a digital doctor education and promotion model establishment system according to claim 4, characterized in that: In step S1, the doctor's image, video and voice information are input into the personal AI digital human database using hyper-realistic AI digital human technology, and the image and voiceprint are created using image learning and voice cloning technology; In image learning, realistic character images are generated through deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. In voice cloning, speech recognition technology, speech synthesis technology, machine learning technology, and machine hearing technology are used to simulate real-person original voices with high fidelity.

6. The promotion solution of a digital doctor education and promotion model establishment system according to claim 4, characterized in that: In step S2, the method for building a database of doctors through the doctor-side digital education promotion model is as follows: S21: Establish an initial database by injecting the knowledge and experience of medical experts in the field as initial audio and video into the total MDV multimodal database to form an initial database of digital doctor image knowledge data; S22: Establish a personal database, and use AIGC service tools to assist doctors in learning medical professional knowledge by using text, pictures, and videos. Based on the initial database of digital doctor image knowledge data, adjust the personal MDV multimodal database to adjust the professional knowledge of the personal digital doctor image to form a personal personalized MDV multimodal database.

7. The promotion solution of a digital doctor education and promotion model establishment system according to claim 4, characterized in that: In step S3, the doctor-side promotion module assists the doctor in making the following steps according to the patient's diagnosis and treatment process: S31: Pre-diagnosis understanding: the digital doctor records the patient's basic condition in advance through questions and answers and patient text input; S32: Improve efficiency during diagnosis. By recording the basic condition of the patient, doctors can understand the patient's condition, save consultation time, and speed up the medical diagnosis. Digital doctors can also educate and popularize scientific examinations, saving time on explaining examination items. S33: Post-diagnosis medical advice combines the medical diagnosis results with the patient's special instructions for the use of medicines, and forms a digital medical advice through the corresponding content in the digital doctor, saving time for medical advice explanation.

8. The promotion solution of a digital doctor education and promotion model establishment system according to claim 4, characterized in that: In step 2, the patient-side digital education promotion model assists patients in diagnosis in the following steps according to the patient's diagnosis and treatment process: Pre-diagnosis knowledge popularization: Before seeing a doctor, patients can communicate with the digital doctor online in the form of questions and answers by inputting text, audio and video information. The digital doctor can also popularize and record the patient's medical problems to help the patient understand the relevant knowledge of the disease. Accompanying during consultation: When seeing a doctor, patients can communicate with digital doctors to obtain detailed information about offline hospitals, such as navigation to doctors' clinics and consultation queue information, as well as scientific information about examination items. When the digital doctor determines that the patient meets the doctor's diagnostic criteria, the patient can make an appointment, thus solving the problem of wasted and mismatched medical resources, such as patients not being able to make an appointment or making the wrong appointment. Post-diagnosis interpretation: After the consultation, patients can communicate with digital doctors to obtain digital medical advice and prescription information, as well as report interpretations, so that they can know and understand their own medical diagnosis results.

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