AI intelligence-based medicine question answering interaction system and method thereof

Abstract

The invention discloses an AI intelligence-based medicine question answering interaction system and method, and the system comprises an interaction module which is used for displaying interaction content through a display interface, and enabling a user to register or log in so as to select and bind an intelligent animation image; the data acquisition module is used for acquiring user input information; the data transmission module is used for feeding back the information acquired by the data acquisition module to the data processing module; the data processing module is used for analyzing and processing the information transmitted by the data transmission module and generating an answer text; the AI module is used for inputting the answer text to the target intelligent animation image and feeding back the answer text to the interaction module; and the manual verification module is used for carrying out manual verification on the interaction content and signing to generate a report after a specific time period after the user inputs the information for the first time, and feeding back the signed report to the interaction module. According to the AI intelligent medicine question answering interaction system, one-to-one service of medicine question answering is realized, and accurate transmission of key information is ensured through manual verification.

Description

Technical Field

[0001] The present invention relates to the field of medical intelligent question-answering technology, and relates to but is not limited to an AI-based medical question-answering interactive system and method. Background Art

[0002] In recent years, the rapid development of the internet, multimedia technology, and AI large-scale modeling has driven the widespread adoption of mobile phones, tablets, and other terminal devices. Online communication has also gradually matured from its initial stages of development and exploration. In the medical field, online intelligent question-and-answering is experiencing rapid development. When people feel unwell, they often search online for similar symptoms to determine whether they need to visit a hospital. Once the ailment is confirmed, they will continue to search online for relevant precautions.

[0003] However, current online medical Q&A platforms still face numerous challenges. First, true one-on-one interaction is difficult to achieve, failing to meet the needs of users for in-depth communication with professionals. Second, some diseases experience worsening symptoms at night and lessening symptoms during the day, but online support is often less available at night, making 24 / 7 service impossible. Finally, insufficient recognition accuracy prevents the precise transmission of key information and the provision of personalized medical advice, making it difficult to meet people's expectations for high-quality online medical consultations. Summary of the Invention

[0004] Based on this, the embodiment of the present invention provides an AI-based medical question-answering interactive system and method, aiming to solve the defects of the existing technology.

[0005] The technical solution of the embodiment of the present invention is achieved as follows: An embodiment of the present invention provides an AI-based interactive medical question-and-answer system, comprising: An interactive module is used to display interactive content through a display interface, and allows users to register or log in to select and bind an intelligent animated image; a data acquisition module is used to obtain user input information, which includes voice, image, physical examination report, and user positioning information; a data transmission module is used to feed back the information obtained by the data acquisition module to the data processing module; a data processing module is used to analyze and process the information transmitted by the data transmission module and generate an answer text; an AI module includes multiple intelligent animated images, which are used to input the answer text to the target intelligent animated image and feed it back to the interactive module; wherein the target intelligent animated image is the intelligent animated image bound after the user logs in; a manual verification module is used to manually verify and sign the interactive content after a specific period of time from the first time the user inputs information, and generate a report, feed back the signed report to the interactive module and unbind the target intelligent animated image.

[0006] In a specific embodiment, the data processing module includes: a preprocessing module, which is used to obtain factor information based on the transmitted information; a base large model module, which uses the DeepSeek-V3-0324 model to obtain different phrase sequences based on the obtained factor information; a fine-tuning module, which uses LoRA technology to fine-tune the DeepSeek-V3-0324 model in a vertical field knowledge base according to different phrase sequences to generate an answer text; the knowledge base includes at least a large number of authoritative health books, encyclopedia knowledge, medical classics, clinical guidelines, drug instructions, medical research papers, medical cases, doctor information and hospital appointment interfaces.

[0007] In a specific embodiment, the step of obtaining factor information based on the transmitted user voice information includes: Speech information processing: The audio signal is converted into spectral features through the speech spectrogram to obtain feature vectors; the audio data is subjected to noise reduction processing to improve the audio quality; the acoustic model calculates the probability of each feature vector on the acoustic feature based on the acoustic characteristics to obtain factor information.

[0008] Image information processing: noise reduction on images; feature extraction, using convolutional neural networks to extract features from images as factor information; disease diagnosis, classifying diseases on images, using segmentation models to accurately segment lesion areas, and extracting lesion boundaries and area information as factor information; quality assessment, using image analysis technology to detect artifacts in X-ray and CT images, and scoring image quality based on image clarity and contrast indicators as factor information; image segmentation, using deep learning segmentation models to separate cells and tissue structures in pathological sections, extract key areas of cell nuclei and cytoplasm, and obtain the morphology, size, and arrangement characteristics of cell nuclei as factor information; using optical character recognition technology to identify text information, QR codes, and barcodes on drug packaging as factor information.

[0009] In a specific embodiment, the interaction module includes: a registration and login submodule, which is used for user registration or login and obtaining a user ID; a user input submodule, which is used for the user to input information; the information includes voice information, image information, historical physical examination reports, and user location information; a display interface, which is used to display multiple intelligent animation images and interactive content of the AI ​​module, allowing users to select intelligent animation images and determine whether the problem is solved and whether they need to ask again.

[0010] In a specific embodiment, the report includes a basic information part, a manual verification part, a consultation and advice part, a personalized medicine and precision medicine part, an intelligent diagnosis and treatment assistance part, a medication recommendation part, a medical resource navigation and appointment part, a data security and privacy protection part, a follow-up part and an attachment part.

[0011] On the other hand, an embodiment of the present invention provides an AI-based interactive method for medical question-answering, comprising the following steps: In response to user registration or login, multiple intelligent animated characters in the AI ​​module are displayed on the display interface of the interaction module for the user to select a target intelligent animated character and bind it; The data acquisition module obtains the user input information and transmits it to the data processing module through the data transmission module; The data processing module analyzes the user input information, generates an answer text, feeds the answer text back to the target intelligent animated image in the AI ​​module, and displays the question and answer record in real time through the display interface; After a specific period of time from the first time the user inputs information, the interactive content is manually verified and signed for confirmation through the manual verification module, and a report is generated. The report is fed back to the display interface for display, and the target intelligent animation image is unbound.

[0012] Compared with the prior art, the beneficial effects of the present invention include at least: The AI ​​intelligent medical question-and-answer interactive system and method of the present invention realizes one-to-one medical question-and-answer service and 24-hour uninterrupted service, and improves the recognition accuracy through manual verification, ensures the accurate transmission of key information, provides users with personalized medical advice, and satisfies users' high-quality online medical consultation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive work, among which: Figure 1 A schematic diagram of the structure of an AI-based interactive medical question-and-answer system provided in an embodiment of the present invention; Figure 2 A schematic diagram of the detailed structure of an AI-based interactive medical question-and-answer system provided in an embodiment of the present invention; Figure 3 A flowchart of an AI-based interactive method for medical question-and-answer sessions provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, 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 part of the embodiments of the present invention, rather than all the embodiments. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention. 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.

[0015] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0016] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present invention are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present invention described here can be implemented in an order other than that illustrated or described here.

[0017] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art in the art to which the embodiments of the present invention pertain. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless specifically defined as herein, should not be interpreted in an idealized or overly formal sense.

[0018] Example 1 See Figure 1 , Figure 1This is a schematic diagram of the structure of an AI-based interactive medical question-and-answer system. This embodiment provides an AI-based interactive medical question-and-answer system, comprising an interactive module for displaying interactive content through a display interface and allowing users to register or log in to select and bind an intelligent animated avatar; a data acquisition module for acquiring user input information, including voice, images, physical examination reports, and user location information; a data transmission module for feeding the information acquired by the data acquisition module back to a data processing module; a data processing module for analyzing and processing the information transmitted by the data transmission module and generating a textual response; an AI module comprising multiple intelligent animated avatars for inputting the textual response into a target intelligent animated avatar and feeding it back to the interactive module; wherein the target intelligent animated avatar is the intelligent animated avatar bound to the user after login; and a manual verification module for manually verifying and signing the interactive content after a specific period of time from the first time the user inputs information, generating a report, feeding the signed report back to the interactive module, and unbinding the target intelligent animated avatar. A strict privacy protection mechanism is established within this system to ensure that the use of user data complies with laws, regulations, and ethical requirements. For example, the system must obtain explicit authorization from the user before using user data, and it can only be used for medical diagnosis and treatment purposes. Reports can be generated based on user needs, typically 48 hours after the user first entered their information.

[0019] Specifically, the data transmission module uses advanced encryption technology to ensure the security and privacy of user data. For example, sensitive information such as user genetic data and medical records is stored and transmitted through encryption to prevent data leakage.

[0020] Specifically, if Figure 2As shown, the data processing module includes a preprocessing module, which is used to obtain factor information based on the transmitted information; a base large model module, which uses the DeepSeek-V3-0324 model to obtain different phrase sequences based on the obtained factor information; and a fine-tuning module, which uses LoRA technology to fine-tune the DeepSeek-V3-0324 model based on different phrase sequences to generate response text. The knowledge base includes at least a large number of authoritative health books, encyclopedias, medical classics, clinical guidelines, drug instructions, medical research papers, medical case studies, doctor information, and a hospital appointment interface. This constructs a comprehensive and professional medical knowledge base that recommends nearby hospitals and specialists based on the user's location, disease type, and needs, and provides online appointment services. For example, if a user enters "cardiologist," the system can recommend nearby cardiologists and provide an appointment link. Telemedicine and online consultation: Integrating a telemedicine platform allows users to directly consult with doctors online or via video chat through the system to obtain professional medical advice. LoRA enables rapid model adjustment by inserting a low-rank matrix into the model's key weight matrix, making it more adaptable to specific tasks in the medical field. This system can provide precise recommendations based on individual characteristics: Based on a user's genetic test data, it provides personalized treatment plans and medication recommendations. For example, based on the specific gene variants a user carries, it can recommend more suitable medications and treatment options to avoid adverse drug reactions. It can also provide personalized health advice and disease prevention plans based on the user's age, gender, and lifestyle data (such as diet, exercise, and sleep). For example, for office workers with long periods of sedentary life, the system can provide appropriate exercise recommendations and preventative measures for cervical spondylosis. Furthermore, based on a comprehensive diagnostic model powered by machine learning and deep learning, it can combine multi-dimensional data such as symptoms, physical signs, laboratory test results, and imaging studies to provide more accurate disease diagnoses. For example, the system can analyze a user's symptoms, blood test results, CT scans, and other data to comprehensively determine the possible disease the user has. Based on the latest clinical guidelines and evidence-based medicine, it can provide optimized treatment plans for users. For example, for a cancer patient, the system can recommend the most suitable chemotherapy regimen, targeted therapy drug, and immunotherapy regimen based on the latest clinical research results.

[0021] Specifically, the method for obtaining factor information based on the transmitted information includes: voice information processing: performing noise reduction processing on audio data to improve the quality of audio; converting the audio signal into spectral features through a voice spectrogram to obtain feature vectors; and calculating the probability of each feature vector on the acoustic features based on the acoustic characteristics by an acoustic model to obtain factor information.

[0022] Image information processing: Denoise images; Feature extraction: Using convolutional neural networks to extract image features as factor information; Disease diagnosis: Classify diseases in images, accurately segment lesions using segmentation models, and extract lesion boundaries and area information as factor information; Quality assessment: Detect artifacts in X-ray and CT images using image analysis techniques, and score image quality based on image clarity and contrast as factor information; Image segmentation: Using deep learning segmentation models to separate cells and tissue structures in pathological sections, extract key regions of the cell nucleus and cytoplasm, and obtain the morphology, size, and arrangement characteristics of the cell nucleus as factor information; Use optical character recognition technology to recognize text information, QR codes, and barcodes on drug packaging as factor information. Denoise images: Use Gaussian filtering and median filtering to remove noise from images, enhance the visual quality of images through contrast enhancement and histogram equalization, and normalize image data to a uniform range for easy subsequent processing. The system supports users to ask questions through voice, text, and images. For example, users can upload images of drug packaging, and the system uses image recognition technology to identify the drug name and provide relevant information. Users can also ask questions through voice, and the system interacts through voice recognition and speech synthesis technology. Optical character recognition (OCR) technology is used to identify textual information on drug packaging, including drug name, indications, usage, and dosage, supporting multiple languages ​​and fonts to improve recognition accuracy and robustness. QR codes and barcodes on drug packaging are recognized to enable drug traceability and authenticity verification. The system connects to the drug manufacturer's database to obtain information such as the drug's production date, batch, and sales channel. This information is integrated to generate a complete drug information report, allowing users to quickly obtain relevant drug knowledge.

[0023] This system builds a comprehensive knowledge base that encompasses not only Traditional Chinese Medicine (TCM) knowledge but also modern (Western) medicine, covering disease diagnosis, treatment, medication information, surgical methods, medical equipment, and other aspects. For example, for a specific disease (such as diabetes), the system can simultaneously provide information on TCM syndrome differentiation and treatment, as well as Western medicine information on blood sugar monitoring and insulin therapy. Interdisciplinary knowledge integration: Integrating knowledge from multiple disciplines, including pharmacology, physiology, pathology, clinical medicine, and preventive medicine, enables the system to provide comprehensive medical knowledge answers. For example, when it comes to drug side effects, the system can not only explain the drug's pharmacological effects but also combine physiological knowledge to explain its effects on the human body.

[0024] The data processing module uses a "question" and "response" model for processing. Specifically, the data processing module takes user-entered questions as input and generates corresponding responses by invoking the fine-tuned DeepSeek-V3-0324 model. This model not only efficiently handles real-time user queries but also ensures that the system's output answers are highly accurate and professional, further improving the system's overall performance and user experience.

[0025] Specifically, if Figure 2 As shown, the interaction module includes: a registration and login submodule, which is used for user registration or login and obtaining user ID; a user input submodule, which is used for user input of information; the information includes voice information, image information, historical physical examination reports, and user location information; a display interface, which is used to display multiple intelligent animation images and interactive content of the AI ​​module, allowing users to select intelligent animation images and judge whether the problem is solved and whether they need to ask again. Furthermore, the interaction module uses Vue 3 and Flask as the main technical framework. As a front-end framework, Vue 3 provides efficient and flexible user interface development capabilities, which can provide users with a smooth and friendly interactive experience. As a back-end framework, Flask is lightweight and easy to expand. It can efficiently process user requests, realize seamless connection between the front and back ends, and ensure stable operation and efficient response of the system.

[0026] Specifically, the report includes basic information, manual verification, consultation recommendations, personalized medicine and precision medicine, intelligent diagnosis and treatment assistance, medication recommendations, medical resource navigation and appointment booking, data security and privacy protection, follow-up, and attachments. The basic information section includes: user information, user name (optional); consultation date and time; consultation method (voice, text, image, etc.); user location (if applicable, for medical resource recommendation); consultation topic; an overview of the user's main consultation question; the nature of the question and the medical field involved, as initially analyzed by the data processing module; the data processing module's initial understanding of the user's question, as well as the data processing module's initial judgment of the disease type and possible treatment methods.

[0027] The manual verification part includes: detailed verification of user questions including symptoms, medical history and previous treatments; verification and adjustment of data processing module analysis; verification process records; detailed records of manual communication with users including questions and answers.

[0028] The consultation and advice section includes: Western medicine knowledge including disease diagnosis, treatment, drug information, surgical methods, medical equipment, etc.; Traditional Chinese Medicine knowledge including dialectical methods, Chinese herbal prescriptions, acupuncture and massage, etc.; interdisciplinary knowledge including the combination of multidisciplinary knowledge such as pharmacology, physiology, pathology, and the overall picture of the problem; recommended measures including Western medicine suggestions (drug treatment plans, surgical suggestions, examination items, etc.); Traditional Chinese Medicine suggestions (Chinese herbal prescriptions, acupuncture and massage plans, diet therapy suggestions, etc.); lifestyle suggestions including personalized suggestions on diet, exercise, sleep, etc.; precautions including: precautions for drug use (dosage, time, interactions, etc.), precautions during treatment (such as exercise intensity, dietary taboos, etc.).

[0029] The personalized medicine and precision medicine section includes genetic information and personalized treatment; if the user provides genetic test data, the report should include an interpretation of the genetic test results; personalized treatment plans and drugs recommended based on genetic information; lifestyle and health advice; and personalized health advice and disease prevention plans based on the user's lifestyle data (age, gender, diet, exercise, sleep, etc.).

[0030] The intelligent diagnosis and treatment assistance part includes the results of the comprehensive diagnostic model; the judgment results of the system comprehensive diagnostic model, including possible disease diagnosis and diagnostic basis (symptoms, test results, etc.); treatment plan optimization; based on the latest clinical guidelines and evidence-based medicine evidence, recommended optimized treatment plans include drug treatment, surgical treatment, rehabilitation treatment and other suggestions.

[0031] The medication recommendations section includes medication usage suggestions; medication selection: recommends the most suitable medication based on the user's specific condition and physical condition; medication dosage: clarifies the recommended medication dosage, including the dosage per dose and the number of times per day; medication time: recommends the best time to take the medication (such as before meals, after meals, before bed, etc.); Medication treatment course: Describes the medication treatment course, including short-term treatment and long-term management; Drug adverse reaction monitoring recommendations; Common adverse reactions: Lists common adverse reactions that may occur with the drug, such as nausea, vomiting, rash, etc.; Monitoring methods: Suggests how users should monitor adverse reactions during medication, such as regular blood tests, liver and kidney function checks, etc.; Countermeasures: If adverse reactions occur, measures to be taken, such as suspending medication, seeking medical attention in a timely manner, etc.; Combination medication recommendations Drug interactions: If the user is currently using other drugs, provide combination medication recommendations to avoid drug interactions; Synergistic treatment: Recommends whether other drugs need to be used in combination to enhance the therapeutic effect, such as the combined use of antibiotics and immunomodulators; Dose adjustment recommendations Individual differences: Based on the user's age, weight, liver and kidney function and other factors, recommends whether the drug dosage needs to be adjusted; Therapeutic response: Based on the user's therapeutic response, recommends whether the dosage needs to be adjusted, such as dosage adjustment when the drug is ineffective or adverse reactions occur.

[0032] The medical resource navigation and appointment section includes hospital and doctor recommendations; recommendations for nearby hospitals and specialist doctors; provision of online appointment links or contact information; telemedicine and online consultation; and provision of telemedicine platform information, allowing users to directly conduct online consultations or video consultations with doctors through the system.

[0033] The data security and privacy protection section includes data encryption and privacy protection; an explanation of the encrypted storage and transmission methods of user data; and an explanation of the privacy protection mechanism, including data usage authorization and compliance.

[0034] The follow-up part includes: follow-up plan: formulate a follow-up plan based on the nature of the user's problem, such as regular review, drug treatment effect evaluation, etc.; contact information: provide users with contact information for further consultation, including the consultation platform website, customer service phone number, etc.

[0035] Example 2 See Figure 3 , Figure 3 The flowchart of the interactive method for medical question-answering based on AI intelligence is applied to the interactive system for medical question-answering based on AI intelligence provided in this embodiment, and specifically includes the following steps: Step S110 , in response to user registration or login, multiple intelligent animated characters in the AI ​​module are displayed on the display interface of the interaction module for the user to select a target intelligent animated character and bind it; Step S120, obtaining user input information through the data acquisition module and transmitting it to the data processing module through the data transmission module; Step S130: Analyze the user input information through the data processing module, generate a response text, feed the response text back to the target intelligent animated image in the AI ​​module, and display the question and answer record in real time through the display interface; Step S140: After a specific period of time since the user first inputs information, the interactive content is manually verified and signed for confirmation through the manual verification module, and a report is generated. The report is fed back to the display interface for display, and the target intelligent animated image is unbound.

[0036] The entire method realizes one-to-one medical Q&A service with 24-hour uninterrupted service, and improves recognition accuracy through manual verification, ensuring the accurate transmission of key information, providing users with personalized medical advice, and meeting users' needs for high-quality online medical consultation.

[0037] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. The serial numbers of the above-mentioned embodiments of the present invention are for description only and do not represent the advantages and disadvantages of the embodiments.

[0038] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0039] In the several embodiments provided herein, it should be understood that the disclosed methods can be implemented in other ways. The methods disclosed in the several method embodiments provided herein can be combined arbitrarily, unless they conflict, to produce new method embodiments. The features disclosed in the several method embodiments provided herein can be combined arbitrarily, unless they conflict, to produce new method embodiments.

[0040] The above description is merely an embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An AI-based interactive medical question-answering system, characterized by: include: The interactive module is used to display interactive content through the display interface and allow users to register or log in to select and bind smart animated characters; A data acquisition module is used to obtain user input information; the user input information includes voice, image, physical examination report, and user location information; A data transmission module, used to feed back the information acquired by the data acquisition module to the data processing module; A data processing module, configured to analyze and process the information transmitted by the data transmission module and generate a response text; The AI ​​module includes multiple intelligent animated characters, which are used to input the answer text into a target intelligent animated character and feed it back to the interaction module; wherein the target intelligent animated character is the intelligent animated character bound to the user after logging in; The manual verification module is used to manually verify and sign the interactive content after a specific period of time since the user first input the information, generate a report, feed the signed report back to the interactive module, and unbind the target intelligent animation image.

2. The AI ​​intelligent medical question-answering interactive system according to claim 1 is characterized in that: The data processing module includes: A preprocessing module, used to obtain factor information based on the transmitted information; The base large model module uses the DeepSeek-V3-0324 model to obtain different phrase sequences based on the obtained factor information; The fine-tuning module uses LoRA technology to fine-tune the DeepSeek-V3-0324 model based on different phrase sequences to perform vertical field knowledge base fine-tuning to generate answer text; the knowledge base includes at least a large number of authoritative health books, encyclopedia knowledge, medical classics, clinical guidelines, drug instructions, medical research papers, medical cases, doctor information and hospital appointment interfaces.

3. The AI ​​intelligent medical question-answering interactive system according to claim 2 is characterized in that: The method for obtaining factor information according to the transmitted information includes: Speech information processing: The audio signal is converted into spectral features through the speech spectrogram to obtain feature vectors. The acoustic model calculates the probability of each feature vector on the acoustic feature based on the acoustic characteristics to obtain factor information. Image information processing: denoising the image; feature extraction, using convolutional neural networks to extract features from the image as factor information; disease diagnosis, classifying the image, segmenting the lesion area using a segmentation model, extracting the boundary and area information of the lesion as factor information; quality assessment, detecting artifacts in X-ray and CT images through image analysis technology, and scoring the image quality based on the image clarity and contrast indicators as factor information; image segmentation, using a deep learning segmentation model to separate cells and tissue structures in pathological sections, extracting key areas of the cell nucleus and cytoplasm, and obtaining the morphology, size, and arrangement characteristics of the cell nucleus as factor information; using optical character recognition technology to identify text information, QR codes, and barcodes on drug packaging as factor information.

4. The AI ​​intelligent medical question-answering interactive system according to any one of claims 1 to 3, characterized in that: The interaction module includes: Registration and login submodules are used for user registration or login and obtaining user ID; The user input submodule is used for the user to input information; the information includes voice information, image information, historical physical examination reports, and user location information; The display interface is used to display multiple intelligent animation images and interactive content of the AI ​​module, allowing users to select intelligent animation images and judge whether the problem is solved and whether they need to ask again.

5. The AI ​​intelligent medical question-answering interactive system according to any one of claims 1 to 3, characterized in that: The report includes: Basic information section, manual verification section, consultation and advice section, personalized medicine and precision medicine section, intelligent diagnosis and treatment assistance section, medication advice section, medical resource navigation and appointment section, data security and privacy protection section, follow-up section and attachment section.

6. An AI-based interactive method for medical question-answering, characterized in that: The method of applying the AI ​​intelligent medical question-answering interactive system according to any one of claims 1 to 5 comprises: In response to user registration or login, multiple intelligent animated characters in the AI ​​module are displayed on the display interface of the interaction module for the user to select a target intelligent animated character and bind it; The data acquisition module obtains the user input information and transmits it to the data processing module through the data transmission module; The data processing module analyzes the user input information, generates an answer text, feeds the answer text back to the target intelligent animated image in the AI ​​module, and displays the question and answer record in real time through the display interface; After a specific period of time since the user first inputs information, the interactive content is manually verified and signed for confirmation through the manual verification module, and a report is generated. The report is fed back to the display interface for display, and the target intelligent animated image is unbound.

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