Analysis method of traditional Chinese medicine encephalopathy risk assessment data containing credibility factors

Abstract

The invention discloses a method for analyzing traditional Chinese medicine encephalopathy risk assessment data containing credibility factors, and relates to the technical field of traditional Chinese medicine encephalopathy risk assessment, which comprises the following steps: S1, establishing a doctor experience assessment system: assessing experience levels for doctors according to quantitative standards by formulating the quantitative standards of doctor experience, and establishing the doctor experience assessment system; and obtaining a doctor weight experience level, and taking the doctor weight experience level as a credibility factor to be included in risk assessment. According to the traditional Chinese medicine encephalopathy risk assessment data analysis method containing the credibility factors, the credibility factors such as various symptom expressions, examination data, medical history and treatment compliance of the patient are comprehensively considered, the risk condition of the patient is comprehensively assessed, the one-sidedness of single-factor assessment is avoided, and the diagnosis result is more accurate and reliable; a multi-doctor consultation mechanism is implemented, doctors with different experience levels analyze and evaluate the condition of a patient from multiple angles, and a final result is determined by using a majority voting principle.

Description

Technical Field

[0001] The present invention relates to the technical field of TCM encephalopathy risk assessment, and in particular to a method for analyzing TCM encephalopathy risk assessment data including a credibility factor. Background Art

[0002] Brain disease in TCM refers to the use of TCM theories and methods to study and treat brain-related diseases. In TCM theory, the brain is an extraordinary organ, closely related to the five internal organs. The scope of brain disease in TCM is relatively broad, including headaches, dizziness, stroke, dementia, epilepsy, insomnia and other symptoms. TCM has a unique theoretical system for understanding brain disease. It is believed that the occurrence of brain disease is related to many factors such as the six exogenous pathogens, the seven internal emotions, improper diet, excessive work and rest, and old age. Its pathogenesis mainly involves qi and blood deficiency, liver and kidney yin deficiency, phlegm and turbidity obstruction, and blood stasis. In terms of diagnosis, TCM uses the four methods of observation, auscultation, inquiry and palpation to observe the patient's symptoms, tongue and pulse, and make a comprehensive judgment on the condition.

[0003] However, with the continuous development of medical technology, TCM plays an increasingly important role in the diagnosis and treatment of encephalopathy; however, TCM encephalopathy risk assessment currently faces some challenges: in actual TCM clinics, doctors with different experience levels may have different TCM encephalopathy risk assessment results for the same patient. For example, a young TCM practitioner and an experienced old TCM practitioner may have different judgments on the patient's tongue and pulse, which leads to doubts about the credibility of the risk assessment, which brings confusion to patients and affects subsequent treatment decisions. Summary of the invention

[0004] In order to solve the above technical problems, the present invention is implemented by the following technical solutions: a method for analyzing TCM encephalopathy risk assessment data including credibility factors, comprising the following steps:

[0005] S1. Establish a doctor experience evaluation system: by formulating quantitative standards for doctor experience, the doctor's experience level is evaluated according to the quantitative standards, and the doctor's weighted experience level is obtained. The doctor's weighted experience level is included in the risk assessment as a credibility factor. Among them, the quantitative standards include the number of years of medical practice, the number of relevant academic research participated in, and the number of successful treatment cases; for example, the diagnosis results given by experienced doctors can be appropriately increased in credibility weight;

[0006] S2. Based on the obtained doctor weight experience level, collect the patient's encephalopathy information, and extract weight modal features from the TCM encephalopathy information, record them as TCM key features, and perform data cleaning on the TCM key features, remove duplicate data, identify and process outliers, and fill in missing data to obtain TCM encephalopathy data;

[0007] S3. Analyze and process the collected TCM encephalopathy data in combination with credibility factors, and construct a TCM encephalopathy risk assessment model. Through this model, the risk of TCM encephalopathy in patients is assessed and predicted, and the risk prediction results are obtained to provide a scientific basis for the treatment and prevention of patients;

[0008] S4. Implement a multi-doctor consultation mechanism: For the risk assessment of TCM encephalopathy, based on the risk prediction results and TCM encephalopathy data, organize doctors with different experience levels to consult, combine the opinions of all doctors, and use the majority voting principle to determine the final risk assessment result. This can reduce the subjectivity of a single doctor's judgment and improve the credibility of the assessment results;

[0009] Regularly organize TCM doctors to participate in professional training to update their understanding and diagnostic skills of TCM brain diseases; at the same time, establish a doctor communication platform to allow them to share experiences and cases and promote the common improvement of diagnostic levels. This can narrow the diagnostic differences between different doctors and improve the overall credibility of risk assessment.

[0010] Preferably, the credibility factors in step S1 include the patient's symptoms, examination data, patient history and treatment compliance factors, and the doctor's weighted experience level.

[0011] Preferably, the TCM encephalopathy data in step S2 includes traditional TCM diagnosis information and modern medical examination data; traditional TCM diagnosis information includes symptom manifestations, tongue image, and pulse image; modern medical examination data includes imaging examination data, laboratory examination data, neuroelectrophysiological examination data, psychological assessment, and sleep monitoring.

[0012] Preferably, the step S1 comprises:

[0013] S11: Determine the evaluation indicators, including years of medical practice, number of academic research participated in, and number of successful treatment cases;

[0014] S12: Quantify the evaluation indicators to obtain quantified years of medical practice, quantified academic research and quantified treatment cases;

[0015] S13: Weighted sum of quantified years of medical practice, quantified academic research, and quantified treatment cases to obtain a comprehensive score;

[0016] S14: Based on the range of the comprehensive score, the experience level of the doctors is divided into different levels, including primary, intermediate and senior; each level corresponds to a different credibility weight, which is used for the subsequent TCM encephalopathy risk assessment to obtain the doctor's experience level;

[0017] S15: Use experience level as a credibility factor in TCM encephalopathy risk assessment, and assign risk assessment opinion weights based on the experience level to obtain the doctor's weighted experience level.

[0018] Preferably, the comprehensive score in step S13 :

[0019] Suppose the score of the quantitative medical practice years is , the score for quantitative academic research is , the score of the quantitative treatment case is , the weight of years of medical practice is , the academic research weight is , the weight of successful treatment cases is ,and ; Comprehensive score .

[0020] Preferably, the evaluation indicators in step S12 are quantified, the years of medical practice are graded and quantified and scored to obtain quantified years of medical practice; the number of academic research is quantified and scored according to level, number of publications and quality to obtain quantitative academic research; successful treatment cases are quantified and scored according to complexity and effect to obtain quantitative treatment cases;

[0021] The process of establishing a physician experience evaluation system is as follows: determine the physician's years of medical practice, the number of academic research studies he / she has participated in, and the number of successful treatment cases, and then quantify the evaluation indicators; for years of medical practice, grade and quantify the scores according to different ranges of years; set 0-5 years as junior, with a corresponding quantitative score of 40 points; 6-10 years as intermediate, with a corresponding quantitative score of 60 points; more than 10 years as senior, with a corresponding quantitative score of 80 points; among them, for years of medical practice: start from the time the physician obtains the qualification to practice, and count the total number of years he / she has been engaged in medical work; the longer the years, it is generally believed that the physician has relatively more experience accumulated in clinical practice; for the number of academic research studies he / she has participated in: it includes scientific research projects related to TCM brain diseases, academic papers published, and academic conferences attended; it reflects the physician's in-depth research and exploration in the field of TCM brain diseases, which helps to improve his / her professional level and diagnostic ability; for successful Number of treatment cases: Statistics on the number of successful cases of doctors in TCM brain disease treatment; successful cases can be judged based on the patient's recovery and the degree of symptom improvement; for the number of academic research participation, quantitative scoring is performed based on the level of scientific research projects, the number and quality of academic papers published, and the importance of participating in academic conferences, and quantitative academic research is obtained, that is, the score after the number of academic research participation is quantified; among them, the level of scientific research projects includes national, provincial, and municipal levels; the quality of academic papers includes core journals and ordinary journals; for the number of successful treatment cases, quantitative scoring is performed based on the complexity of the cases and the treatment effect, and quantitative treatment cases are obtained, that is, the corresponding score after the number of successful treatment cases is quantified; higher scores are given to the successful treatment of complex cases, and lower scores are given to the successful treatment of general cases; at the same time, the follow-up of patients can be considered, and cases with long-term stable recovery will have higher scores;

[0022] The process of collecting the TCM encephalopathy data of the patient in step S2 is as follows:

[0023] The process of collecting information about traditional Chinese medicine diagnosis is as follows:

[0024] Regarding symptom manifestations, we asked patients in detail about their encephalopathy-related symptoms, including headache, dizziness, memory loss, limb numbness, and speech impairment. We also recorded the specific manifestations, duration, and frequency of symptoms.

[0025] And by observing the patient's demeanor, complexion, and actions, more clues related to the condition can be obtained; for example, pale complexion may indicate insufficient Qi and blood, and slow movements may be related to brain lesions;

[0026] The process of collecting tongue images is as follows: For patients to stick out their tongues: let the patients stick out their tongues naturally and observe the shape, color and coating of the tongue; For recording characteristics: record the size, fatness, presence or absence of cracks and tooth marks of the tongue; observe whether the color of the tongue is light red, red or purple; check the thickness, color and moistness of the tongue coating; For collecting pulse images: feel the pulse: the doctor touches the patient's pulse with his fingers to feel the strength, frequency and rhythm of the pulse; determine the pulse: according to the characteristics of the pulse, judge the different pulse types of floating, sinking, slow, rapid and stringy, and record them;

[0027] The process of data collection for modern medical examinations is as follows:

[0028] For imaging examination data:

[0029] For head CT: arrange for patients to undergo head CT examination to obtain structural images of the brain; doctors interpret the images to observe whether there are lesions such as bleeding, infarction, tumors, and hydrocephalus; for head MRI: patients undergo head MRI examination to obtain clearer images of brain soft tissues; focus on observing white matter lesions, early conditions of cerebral infarction, and brain tumors; for cerebral angiography DSA: patients suspected of cerebrovascular lesions undergo DSA examination; doctors analyze angiography images to determine the morphology of cerebral blood vessels, the degree of stenosis, and the presence of aneurysms;

[0030] The process for laboratory test data is:

[0031] For blood biochemical examination: collect blood samples from patients to test indicators of liver and kidney function, blood sugar, blood lipids, and electrolytes; for coagulation function examination: test coagulation function indicators, including prothrombin time, partial thromboplastin time, and platelet count; for inflammatory indicators: test inflammatory indicators, including C-reactive protein and erythrocyte sedimentation rate; for specific biomarkers: test specific biomarkers, including brain natriuretic peptide and neuron-specific enolase;

[0032] The process for neurophysiological examination data is:

[0033] For EEG: patients wear EEG electrodes to record the electrical activity of the brain; doctors analyze the EEG results to determine whether there are signs of brain disease, including epilepsy and encephalitis; for evoked potentials: evoked potential tests, including visual evoked potentials (VEP), auditory evoked potentials (AEP), and somatosensory evoked potentials (SEP), are performed to detect the conduction function of the nervous system;

[0034] The process for psychological assessment and sleep monitoring is as follows:

[0035] For psychological assessment: use psychological scales to assess patients' cognitive functions and emotional states; including understanding patients' memory, attention, anxiety, and depression through questionnaires; for sleep monitoring: have patients wear sleep monitoring equipment to record their sleep quality and sleep structure; doctors analyze sleep data to determine the relationship between sleep disorders and brain diseases.

[0036] Preferably, step S3 comprises:

[0037] S31: Determine input variables: TCM encephalopathy data and credibility factors;

[0038] S32: For input variables, outliers, erroneous data, and duplicate data were removed to ensure data accuracy and completeness, and different types of data were standardized to have the same dimension and scale for subsequent analysis and modeling. The random forest algorithm was used to automatically learn patterns and rules in the data to predict the risk of TCM encephalopathy;

[0039] S33: Divide the existing data of TCM encephalopathy patients and non-patients into training sets and test sets, use the training set data to train the random forest algorithm, and adjust the model parameters to make the model better fit the training data and improve the prediction accuracy; and use cross-validation technology to evaluate the model performance during the training process to avoid overfitting and obtain a well-trained model;

[0040] S34: Use the test set data to evaluate the trained model, calculate the model's accuracy, recall rate, and F1 value, and evaluate the model's prediction effect; if the model performance is not ideal, perform the following optimizations: adjust the model parameters, try different parameter combinations, and find the optimal parameter settings; feature selection, select the features that contribute most to the model prediction, remove redundant features, and improve the model's efficiency and accuracy;

[0041] S35: After evaluation and optimization, a risk assessment model for TCM encephalopathy is obtained, and the model with the best performance is selected as the risk assessment model for TCM encephalopathy.

[0042] Preferably, the random forest model prediction formula in step S33 is:

[0043] Assume the input feature vector is ,in is the number of features, and the random forest is composed of decision trees, each of which is , ; Calculate the risk probability of TCM encephalopathy, that is, predict the results .

[0044] Preferably, the step S3 further comprises:

[0045] S36: inputting the TCM encephalopathy data of the patient to be predicted into the TCM encephalopathy risk assessment model, and the model outputs the risk probability of the patient suffering from TCM encephalopathy after calculation;

[0046] S37: Risk levels are classified based on risk probability to obtain risk levels, including low risk, medium risk and high risk;

[0047] S38: Output the obtained risk level in the form of a report to obtain a risk prediction result, wherein the risk prediction result includes the patient's basic information, TCM encephalopathy data, credibility factors, risk probability and risk level.

[0048] Preferably, step S4 comprises:

[0049] S41: According to the patient's condition and needs, determine the list of doctors participating in the consultation. The doctors have different levels of experience, including senior experts, middle-aged backbone doctors and young doctors. Ensure that the consulting doctor team covers different professional fields, including TCM internal medicine, neurology, imaging, and laboratory, so as to conduct a comprehensive assessment of TCM encephalopathy from multiple perspectives;

[0050] S42: Organize the patient's TCM encephalopathy data, including traditional TCM diagnosis information and modern medical examination data, and distribute the patient's TCM encephalopathy data to the doctors participating in the consultation in advance, so that they have enough time to familiarize themselves with the patient's condition and provide more targeted opinions during the consultation;

[0051] S43: The consultation organizer presides over the meeting, introduces the basic situation of the patient and the purpose of the consultation, and gives the risk prediction results output by the TCM encephalopathy risk assessment model; based on the risk prediction results, each doctor expresses his or her analysis of the patient's condition and risk assessment opinions in turn, and obtains the doctor's opinion. The doctor, based on his or her professional knowledge and experience, elaborates on the patient's symptoms, interpretation of the test results, possible diagnosis and risk assessment; and during the doctor's opinion, the doctor asks questions, discusses and communicates to further understand the patient's condition and different opinions;

[0052] S44: After all doctors have expressed their opinions, a voting session is conducted. Each doctor evaluates the patient's risk of TCM encephalopathy based on his or her own judgment and selects low risk, medium risk or high risk. The voting results are counted and the final risk assessment result is determined according to the majority voting principle. If the majority of doctors believe that the patient is at low risk, the final risk assessment result is low risk; if the majority of doctors believe that the patient is at medium risk or high risk, it is determined to be medium risk or high risk accordingly.

[0053] S45: Record the consultation results during the consultation process, including the doctor's opinions, voting results and final risk assessment results; summarize the consultation results, including the patient's condition analysis, risk assessment basis and next treatment recommendations; generate a written report based on the consultation results, and feedback the written report to the patient and his / her attending physician to provide a decision-making basis for the patient's treatment and management.

[0054] The present invention provides an analysis method for TCM encephalopathy risk assessment data including credibility factors, which has the following beneficial effects:

[0055] The analysis method of TCM encephalopathy risk assessment data including credibility factors establishes a doctor experience assessment system to assess the experience level of doctors and incorporate it into the risk assessment as a credibility factor. The credibility weight of the opinions of experienced doctors is appropriately increased to reduce diagnostic errors caused by differences in doctor experience, thereby improving the overall diagnostic accuracy. It comprehensively considers credibility factors such as the patient's multiple symptoms, examination data, medical history and treatment compliance, comprehensively assesses the patient's risk status, avoids the one-sidedness of a single factor assessment, and makes the diagnostic results more accurate and reliable. It implements a multi-doctor consultation mechanism, in which doctors with different experience levels analyze and evaluate the patient's condition from multiple angles, and use the majority voting principle to determine the final result, thereby reducing the subjectivity of a single doctor's judgment and improving diagnostic accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 The present invention is a flowchart of a method for analyzing TCM encephalopathy risk assessment data including credibility factors. DETAILED DESCRIPTION

[0057] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0058] like Figure 1As shown, the present invention provides a technical solution: a method for analyzing TCM encephalopathy risk assessment data including credibility factors, comprising the following steps:

[0059] S1. Establish a doctor experience evaluation system: by formulating quantitative standards for doctor experience, the doctor's experience level is evaluated according to the quantitative standards, and the doctor's weighted experience level is obtained. The doctor's weighted experience level is included in the risk assessment as a credibility factor. Among them, the quantitative standards include the number of years of medical practice, the number of relevant academic research participated in, and the number of successful treatment cases; for example, the diagnosis results given by experienced doctors can be appropriately increased in credibility weight;

[0060] S2. Based on the obtained doctor weight experience level, collect the patient's encephalopathy information, and extract weight modal features from the TCM encephalopathy information, record them as TCM key features, and perform data cleaning on the TCM key features, remove duplicate data, identify and process outliers, and fill in missing data to obtain TCM encephalopathy data;

[0061] S3. Analyze and process the collected TCM encephalopathy data in combination with credibility factors, and construct a TCM encephalopathy risk assessment model. Through this model, the risk of TCM encephalopathy in patients is assessed and predicted, and the risk prediction results are obtained to provide a scientific basis for the treatment and prevention of patients;

[0062] S4. Implement a multi-doctor consultation mechanism: For the risk assessment of TCM encephalopathy, based on the risk prediction results and TCM encephalopathy data, organize doctors with different experience levels to consult, combine the opinions of all doctors, and use the majority voting principle to determine the final risk assessment result. This can reduce the subjectivity of a single doctor's judgment and improve the credibility of the assessment results;

[0063] Organize TCM doctors to participate in professional training regularly to update their knowledge and diagnostic skills of TCM encephalopathy; at the same time, establish a doctor exchange platform for them to share experiences and cases and promote the joint improvement of diagnostic level, which can narrow the diagnostic differences between different doctors and improve the overall credibility of risk assessment;

[0064] It should be further explained that, in the specific implementation process, by establishing a doctor experience evaluation system and incorporating it into risk assessment, the credibility of the diagnosis results can be improved; the opinions of experienced doctors are appropriately increased in credibility weight, which helps to more accurately assess the patient's risk of TCM encephalopathy; collecting patients' multi-faceted encephalopathy information and performing data cleaning and filling ensures the accuracy and completeness of the data, providing a reliable basis for subsequent risk assessment; constructing a TCM encephalopathy risk assessment model and combining credibility factors for prediction, providing a scientific basis for patient treatment and prevention; implementing a multi-doctor consultation mechanism reduces the subjectivity of a single doctor's judgment and improves the credibility of the assessment results.

[0065] The credibility factors in step S1 include the patient's symptom manifestation, examination data, patient medical history and treatment compliance factors, and the doctor's weighted experience level.

[0066] The TCM encephalopathy data in step S2 includes traditional TCM diagnosis information and modern medical examination data; the traditional TCM diagnosis information includes symptom manifestation, tongue image, and pulse image; the modern medical examination data includes imaging examination data, laboratory examination data, neuroelectrophysiological examination data, psychological assessment, and sleep monitoring;

[0067] It should be further explained that, during the specific implementation process, the specific content of the credibility factors was clarified, including the patient's symptoms, examination data, patient history, treatment compliance, and physician weighted experience level; these factors taken into consideration can more comprehensively assess the patient's risk status.

[0068] Step S1 includes:

[0069] S11: Determine the evaluation indicators, including years of medical practice, number of academic research participated in, and number of successful treatment cases;

[0070] S12: Quantify the evaluation indicators to obtain quantified years of medical practice, quantified academic research and quantified treatment cases;

[0071] S13: Weighted sum of quantified years of medical practice, quantified academic research, and quantified treatment cases to obtain a comprehensive score;

[0072] S14: Based on the range of the comprehensive score, the experience level of the doctors is divided into different levels, including primary, intermediate and senior; each level corresponds to a different credibility weight, which is used for the subsequent TCM encephalopathy risk assessment to obtain the doctor's experience level;

[0073] S15: Use experience level as a credibility factor in TCM encephalopathy risk assessment, and assign risk assessment opinion weights based on experience level to obtain the doctor's weighted experience level;

[0074] It should be further explained that, during the specific implementation process, the content of TCM encephalopathy data is specified in detail, covering traditional TCM diagnosis information and modern medical examination data, making risk assessment more comprehensive and accurate.

[0075] The comprehensive score in step S13 :

[0076] Suppose the score of the quantitative medical practice years is , the score for quantitative academic research is , the score of the quantitative treatment case is , the weight of years of medical practice is , the academic research weight is , the weight of successful treatment cases is ,and ; Comprehensive score ;

[0077] It should be further explained that, in the specific implementation process, determining the evaluation indicators and quantifying and weighted summing them can scientifically divide the doctors' experience levels and provide a reliable credibility factor for risk assessment; allocating risk assessment opinion weights according to experience levels can enable experienced doctors to play a greater role in risk assessment.

[0078] It should be further explained that in the specific implementation process, the quantitative standards for the number of years of medical practice are as follows: 0-5 years is 30 points; 6-10 years is 60 points; more than 10 years is 90 points; the quantitative standards for the number of academic research participated in: 10 points for participating in a provincial or lower scientific research project, 30 points for a national scientific research project; 5 points for publishing a general journal paper, and 20 points for a core journal paper; a doctor participated in a provincial scientific research project, published two general journal papers and one core journal paper, then the academic research quantitative score is 10+5*2+20=40 points; the quantitative standards for successful treatment cases: 5 points for a general successful case; 15 points for a complex successful case;

[0079] This doctor has 10 general success cases and 5 complex success cases, so the quantitative score of successful treatment cases is 10*5+5*15=125 points; set the weight of years of medical practice w1=0.4, the weight of academic research w2=0.3, and the weight of successful treatment cases w3=0.3; if the doctor has been practicing medicine for 8 years, then the quantitative score of years of medical practice is 60 points; the comprehensive score S=0.4*60+0.3*40+0.3*125=73.5 points; divide the experience level according to the range of the comprehensive score, set 0-60 points as elementary, 61-80 points as intermediate, and 81 points and above as advanced; then this doctor is at the intermediate experience level;

[0080] It should be further explained that, during the specific implementation process, a specific calculation method for the comprehensive score and actual examples were given to make the doctor experience evaluation system more specific and operational.

[0081] In step S12, the evaluation indicators are quantified, and the years of medical practice are graded and quantified to obtain the quantified years of medical practice; the number of academic research is quantified and scored according to the level, number of publications and quality to obtain the quantitative academic research; the successful treatment cases are quantified and scored according to the complexity and effect to obtain the quantitative treatment cases;

[0082] It should be further explained that in the specific implementation process, the process of establishing a doctor's experience evaluation system is as follows: determine the doctor's years of medical practice, the number of academic research studies he / she has participated in, and the number of successful treatment cases, and then quantify the evaluation indicators; for the years of medical practice, grade and quantify the scores according to different ranges of years; set 0-5 years as junior, with a corresponding quantitative score of 40 points; 6-10 years as intermediate, with a corresponding quantitative score of 60 points; more than 10 years as senior, with a corresponding quantitative score of 80 points; among them, for the years of medical practice: start from the time the doctor obtains the qualification to practice, and count the total number of years he / she has been engaged in medical work; the longer the years, it is generally believed that the doctor has accumulated relatively more experience in clinical practice; for the number of academic research studies he / she has participated in: it includes scientific research projects related to TCM brain diseases, academic papers published, and academic conferences attended by the doctor; it reflects the doctor's in-depth research and exploration in the field of TCM brain diseases, which helps to improve his / her professional level and Diagnostic ability; For the number of successful treatment cases: count the number of successful cases of doctors in TCM brain disease treatment; successful cases can be judged according to the patient's recovery status and the degree of symptom improvement; For the number of academic research participation, quantitative scoring is performed according to the level of scientific research projects, the number and quality of academic papers published, and the importance of participating in academic conferences, and quantitative academic research is obtained, that is, the score after the number of academic research participation is quantified; among them, the level of scientific research projects includes national, provincial, and municipal levels; the quality of academic papers includes core journals and ordinary journals; For the number of successful treatment cases, quantitative scoring is performed according to the complexity of the cases and the treatment effect, and quantitative treatment cases are obtained, that is, the corresponding score after the number of successful treatment cases is quantified; higher scores are given to the successful treatment of complex cases, and lower scores are given to the successful treatment of general cases; at the same time, the follow-up of patients can be considered, and cases with long-term stable recovery will have higher scores;

[0083] The weight of years of medical practice is set to 40%, the weight of the number of academic research is set to 30%, and the weight of the number of successful treatment cases is set to 30%. The quantitative scores of the three aspects of years of medical practice, the number of academic research and the number of successful treatment cases are weighted and summed to obtain a comprehensive score; then according to the range of the comprehensive score, the doctor's experience level is divided into different levels, including junior, intermediate and senior; each level corresponds to a different credibility weight, which is used for the subsequent risk assessment of TCM encephalopathy; among them, credibility factors include patients' symptoms, examination data, patient history and treatment compliance; according to the level of experience, weights are assigned to doctors' opinions in risk assessment; the higher the experience level of the doctor, the greater the weight of his opinion in risk assessment; the weight of the opinion of doctors with senior experience level can be set to 0.4, intermediate to 0.3, and junior to 0.2; through the above process, a more scientific and reasonable doctor experience evaluation system can be established to provide reliable credibility factors for TCM encephalopathy risk assessment;

[0084] It should be further explained that, during the specific implementation, the establishment process of the doctor experience evaluation system was explained in detail, including the quantification methods of years of medical practice, number of academic research participation and number of successful treatment cases, as well as the setting of weights; this helps to establish a scientific and reasonable evaluation system and improve the reliability of credibility factors; it also describes in detail the process of collecting patients' TCM encephalopathy data, including the methods of collecting traditional TCM diagnostic information and modern medical examination data, providing an accurate data basis for subsequent risk assessment.

[0085] The process of collecting the TCM encephalopathy data of the patient in step S2 is as follows:

[0086] The process of collecting information about traditional Chinese medicine diagnosis is as follows:

[0087] Regarding symptom manifestations, we asked patients in detail about their encephalopathy-related symptoms, including headache, dizziness, memory loss, limb numbness, and speech impairment. We also recorded the specific manifestations, duration, and frequency of symptoms.

[0088] And by observing the patient's demeanor, complexion, and actions, more clues related to the condition can be obtained; for example, pale complexion may indicate insufficient Qi and blood, and slow movements may be related to brain lesions;

[0089] The process of collecting tongue images is as follows: For patients to stick out their tongues: let the patients stick out their tongues naturally and observe the shape, color and coating of the tongue; For recording characteristics: record the size, fatness, presence or absence of cracks and tooth marks of the tongue; observe whether the color of the tongue is light red, red or purple; check the thickness, color and moistness of the tongue coating; For collecting pulse images: feel the pulse: the doctor touches the patient's pulse with his fingers to feel the strength, frequency and rhythm of the pulse; determine the pulse: according to the characteristics of the pulse, judge the different pulse types of floating, sinking, slow, rapid and stringy, and record them;

[0090] The process of data collection for modern medical examinations is as follows:

[0091] For imaging examination data:

[0092] For head CT: arrange for patients to undergo head CT examination to obtain structural images of the brain; doctors interpret the images to observe whether there are lesions such as bleeding, infarction, tumors, and hydrocephalus; for head MRI: patients undergo head MRI examination to obtain clearer images of brain soft tissues; focus on observing white matter lesions, early conditions of cerebral infarction, and brain tumors; for cerebral angiography DSA: patients suspected of cerebrovascular lesions undergo DSA examination; doctors analyze angiography images to determine the morphology of cerebral blood vessels, the degree of stenosis, and the presence of aneurysms;

[0093] The process for laboratory test data is:

[0094] For blood biochemical examination: collect blood samples from patients to test indicators of liver and kidney function, blood sugar, blood lipids, and electrolytes; for coagulation function examination: test coagulation function indicators, including prothrombin time, partial thromboplastin time, and platelet count; for inflammatory indicators: test inflammatory indicators, including C-reactive protein and erythrocyte sedimentation rate; for specific biomarkers: test specific biomarkers, including brain natriuretic peptide and neuron-specific enolase;

[0095] The process for neurophysiological examination data is:

[0096] For EEG: patients wear EEG electrodes to record the electrical activity of the brain; doctors analyze the EEG results to determine whether there are signs of brain disease, including epilepsy and encephalitis; for evoked potentials: evoked potential tests, including visual evoked potentials (VEP), auditory evoked potentials (AEP), and somatosensory evoked potentials (SEP), are performed to detect the conduction function of the nervous system;

[0097] The process for psychological assessment and sleep monitoring is as follows:

[0098] For psychological assessment: use psychological scales to assess patients' cognitive functions and emotional states; including using questionnaires to understand patients' memory, attention, anxiety, and depression; for sleep monitoring: let patients wear sleep monitoring equipment to record their sleep quality and sleep structure; doctors analyze sleep data to determine the relationship between sleep disorders and encephalopathy;

[0099] Through the above process, the patient's TCM encephalopathy data can be comprehensively collected to provide an accurate basis for subsequent risk assessment.

[0100] Step S3 includes:

[0101] S31: Determine input variables: TCM encephalopathy data and credibility factors;

[0102] S32: For input variables, outliers, erroneous data, and duplicate data were removed to ensure data accuracy and completeness, and different types of data were standardized to have the same dimension and scale for subsequent analysis and modeling. The random forest algorithm was used to automatically learn patterns and rules in the data to predict the risk of TCM encephalopathy;

[0103] S33: Divide the existing data of TCM encephalopathy patients and non-patients into training sets and test sets, use the training set data to train the random forest algorithm, and adjust the model parameters to make the model better fit the training data and improve the prediction accuracy; and use cross-validation technology to evaluate the model performance during the training process to avoid overfitting and obtain a well-trained model;

[0104] S34: Use the test set data to evaluate the trained model, calculate the model's accuracy, recall rate, and F1 value, and evaluate the model's prediction effect; if the model performance is not ideal, perform the following optimizations: adjust the model parameters, try different parameter combinations, and find the optimal parameter settings; feature selection, select the features that contribute most to the model prediction, remove redundant features, and improve the model's efficiency and accuracy;

[0105] S35: After evaluation and optimization, a risk assessment model for TCM encephalopathy is obtained, and the model with the best performance is selected as the risk assessment model for TCM encephalopathy;

[0106] It should be further explained that, in the specific implementation process, the input variables were determined and data processing and model training were performed to improve the data quality and the prediction accuracy of the model; the random forest algorithm was used for prediction, and cross-validation and optimization measures were used to improve the performance and reliability of the model.

[0107] The random forest model prediction formula in step S33 is:

[0108] Assume the input feature vector is ,in is the number of features, and the random forest is composed of decision trees, each of which is , ; Calculate the risk probability of TCM encephalopathy, that is, predict the results ;

[0109] It should be further explained that, in the specific implementation process, the prediction process and accuracy of the model were explained through the random forest model prediction formula and actual cases, providing a specific method and reference for patient risk assessment.

[0110] Patient A was analyzed by the TCM encephalopathy risk assessment model, which showed high accuracy in a large amount of training data, with an accuracy of 80%, a recall rate of 75%, and an F1 value of 77% for previous patients; the low risk probability was set at 0 to 30%, the medium risk at 31% to 60%, and the high risk at 61% and above;

[0111] The TCM encephalopathy data input into the model for patient A included: mild headache symptoms, slightly red tongue, slightly stringy pulse; no obvious abnormalities were found in imaging examinations, all indicators of laboratory examinations were basically normal, and there were no abnormalities in neuroelectrophysiological examinations; psychological assessments showed mild anxiety, and sleep monitoring showed mild insomnia;

[0112] In terms of credibility factors, the experience level of the doctor who is responsible for evaluating this patient is intermediate, and the weight of this level in risk assessment is 0.6; the patient has a family history of the disease, that is, one of the parents has suffered from a mild brain disease, and the treatment compliance is good;

[0113] After the model calculation and comprehensive consideration of various factors, the output is that the patient has a 30% risk of TCM encephalopathy. This risk probability means that under the current data and factors, the patient has a 30% chance of suffering from TCM encephalopathy; therefore, the patient is currently in a low-risk state.

[0114] It should be further explained that, in the specific implementation process, the risk probability is divided into risk levels and output in the form of a report, making the risk prediction results more intuitive and easy to understand, providing clear information for doctors and patients; the risk prediction results include basic patient information, TCM encephalopathy data, credibility factors, etc., providing a comprehensive basis for the comprehensive assessment of the patient's risk status;

[0115] Step S3 also includes:

[0116] S36: inputting the TCM encephalopathy data of the patient to be predicted into the TCM encephalopathy risk assessment model, and the model outputs the risk probability of the patient suffering from TCM encephalopathy after calculation;

[0117] S37: Risk levels are classified based on risk probability to obtain risk levels, including low risk, medium risk and high risk;

[0118] S38: Output the obtained risk level in the form of a report to obtain a risk prediction result, wherein the risk prediction result includes the patient's basic information, TCM encephalopathy data, credibility factors, risk probability and risk level.

[0119] Step S4 includes:

[0120] S41: According to the patient's condition and needs, determine the list of doctors participating in the consultation. The doctors have different levels of experience, including senior experts, middle-aged backbone doctors and young doctors. Ensure that the consulting doctor team covers different professional fields, including TCM internal medicine, neurology, imaging, and laboratory, so as to conduct a comprehensive assessment of TCM encephalopathy from multiple perspectives;

[0121] S42: Organize the patient's TCM encephalopathy data, including traditional TCM diagnosis information and modern medical examination data, and distribute the patient's TCM encephalopathy data to the doctors participating in the consultation in advance, so that they have enough time to familiarize themselves with the patient's condition and provide more targeted opinions during the consultation;

[0122] S43: The consultation organizer presides over the meeting, introduces the basic situation of the patient and the purpose of the consultation, and gives the risk prediction results output by the TCM encephalopathy risk assessment model; based on the risk prediction results, each doctor expresses his or her analysis of the patient's condition and risk assessment opinions in turn, and obtains the doctor's opinion. The doctor, based on his or her professional knowledge and experience, elaborates on the patient's symptoms, interpretation of the test results, possible diagnosis and risk assessment; and during the doctor's opinion, the doctor asks questions, discusses and communicates to further understand the patient's condition and different opinions;

[0123] S44: After all doctors have expressed their opinions, a voting session is conducted. Each doctor evaluates the patient's risk of TCM encephalopathy based on his or her own judgment and selects low risk, medium risk or high risk. The voting results are counted and the final risk assessment result is determined according to the majority voting principle. If the majority of doctors believe that the patient is at low risk, the final risk assessment result is low risk; if the majority of doctors believe that the patient is at medium risk or high risk, it is determined to be medium risk or high risk accordingly.

[0124] S45: Record the consultation results during the consultation process, including the doctor's opinions, voting results and final risk assessment results; summarize the consultation results, including the patient's condition analysis, risk assessment basis and next treatment recommendations; generate a written report based on the consultation results, and feedback the written report to the patient and his / her attending physician to provide a decision-making basis for the patient's treatment and management.

[0125] It should be further explained that, in the specific implementation process, the multi-doctor consultation mechanism ensures that the consulting doctor team covers different professional fields and experience levels, and can conduct a comprehensive assessment of TCM brain diseases from multiple angles; the advance distribution of patient data, hosting of meetings, doctors expressing opinions and voting, etc., ensure the scientificity and fairness of the consultation; record the consultation results and generate written reports, which provide a decision-making basis for the treatment and management of patients and improve the quality and efficiency of medical services.

[0126] Obviously, the described embodiments are only some embodiments 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 and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A method for analyzing TCM encephalopathy risk assessment data including credibility factors, characterized in that: The steps include: S1. Establish a doctor experience evaluation system: by formulating quantitative standards for doctor experience, the experience level of doctors is assessed according to the quantitative standards, and the weighted experience level of doctors is obtained. The weighted experience level of doctors is included in the risk assessment as a credibility factor. Among them, the quantitative standards include years of medical practice, the number of relevant academic research participated in, and the number of successful treatment cases; S2. Based on the obtained doctor weight experience level, collect the patient's encephalopathy information, and extract weight modal features from the TCM encephalopathy information, record them as TCM key features, and perform data cleaning on the TCM key features, remove duplicate data, identify and process outliers, and fill in missing data to obtain TCM encephalopathy data; S3. Analyze and process the collected TCM encephalopathy data in combination with credibility factors, construct a TCM encephalopathy risk assessment model, and use the model to assess and predict the risk of TCM encephalopathy in patients to obtain risk prediction results; S4. Implement a multi-doctor consultation mechanism: For the risk assessment of TCM encephalopathy, based on the risk prediction results and TCM encephalopathy data, organize doctors with different experience levels to consult, summarize the opinions of all doctors, and use the majority voting principle to determine the final risk assessment results.

2. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 1, characterized in that: The credibility factors in step S1 include the patient's symptoms, examination data, patient history and treatment compliance factors, and the doctor's weighted experience level.

3. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 2, characterized in that: The TCM encephalopathy data in step S2 includes traditional TCM diagnosis information and modern medical examination data; traditional TCM diagnosis information includes symptom manifestations, tongue image, and pulse image; modern medical examination data includes imaging examination data, laboratory examination data, neuroelectrophysiological examination data, psychological assessment, and sleep monitoring.

4. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 3, characterized in that: The step S1 comprises: S11: Determine the evaluation indicators, including years of medical practice, number of academic research participated in, and number of successful treatment cases; S12: Quantify the evaluation indicators to obtain quantified years of medical practice, quantified academic research and quantified treatment cases; S13: Weighted sum of quantified years of medical practice, quantified academic research, and quantified treatment cases to obtain a comprehensive score; S14: Based on the range of the comprehensive score, the experience level of the doctors is divided into different levels, including primary, intermediate and senior; each level corresponds to a different credibility weight, which is used for the subsequent TCM encephalopathy risk assessment to obtain the doctor's experience level; S15: Use experience level as a credibility factor in TCM encephalopathy risk assessment, and assign risk assessment opinion weights based on the experience level to obtain the doctor's weighted experience level.

5. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 4, characterized in that: The comprehensive score in step S13 : Assume that the score of the quantitative medical practice years is , the score for quantitative academic research is , the score of the quantitative treatment case is , the weight of years of medical practice is , the academic research weight is , the weight of successful treatment cases is ,and ; Comprehensive score .

6. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 5, characterized in that: In the step S12, the evaluation indicators are quantified, the years of medical practice are graded and quantitatively scored to obtain the quantified years of medical practice; the number of academic research is quantified and scored according to the level, number of publications and quality to obtain the quantitative academic research; the successful treatment cases are quantitatively scored according to the complexity and effect to obtain the quantitative treatment cases.

7. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 6, characterized in that: The step S3 comprises: S31: Determine input variables: TCM encephalopathy data and credibility factors; S32: For input variables, outliers, erroneous data, and duplicate data were removed to ensure data accuracy and completeness, and different types of data were standardized to have the same dimension and scale for subsequent analysis and modeling. The random forest algorithm was used to automatically learn patterns and rules in the data to predict the risk of TCM encephalopathy; S33: Divide the existing data of TCM encephalopathy patients and non-patients into training sets and test sets, use the training set data to train the random forest algorithm, and adjust the model parameters to make the model better fit the training data and improve the prediction accuracy; and use cross-validation technology to evaluate the model performance during the training process to avoid overfitting and obtain a well-trained model; S34: Use the test set data to evaluate the trained model, calculate the model's accuracy, recall rate, and F1 value, and evaluate the model's prediction effect; if the model performance is not ideal, perform the following optimizations: adjust the model parameters, try different parameter combinations, and find the optimal parameter settings; feature selection, select the features that contribute most to the model prediction, remove redundant features, and improve the model's efficiency and accuracy; S35: After evaluation and optimization, a TCM encephalopathy risk assessment model was obtained.

8. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 7, characterized in that: The random forest model prediction formula in step S33 is: Assume the input feature vector is ,in is the number of features, and the random forest is composed of decision trees, each of which is , ; Calculate the risk probability of TCM encephalopathy, that is, predict the results .

9. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 8, characterized in that: The step S3 further comprises: S36: inputting the TCM encephalopathy data of the patient to be predicted into the TCM encephalopathy risk assessment model, and the model outputs the risk probability of the patient suffering from TCM encephalopathy after calculation; S37: Risk levels are classified based on risk probability to obtain risk levels, including low risk, medium risk and high risk; S38: Output the obtained risk level in the form of a report to obtain a risk prediction result, wherein the risk prediction result includes the patient's basic information, TCM encephalopathy data, credibility factors, risk probability and risk level.

10. The method for analyzing TCM encephalopathy risk assessment data including credibility factors according to claim 9, characterized in that: The step S4 comprises: S41: Determine the list of doctors participating in the consultation based on the patient's condition and needs. The doctors have different experience levels, including senior experts, middle-aged backbone doctors and young doctors; S42: Organize the patient's TCM encephalopathy data, including traditional TCM diagnosis information and modern medical examination data, and distribute the patient's TCM encephalopathy data to the doctors participating in the consultation in advance; S43: The consultation organizer presides over the meeting, introduces the basic situation of the patient and the purpose of the consultation, and gives the risk prediction results output by the TCM encephalopathy risk assessment model; based on the risk prediction results, each doctor expresses his or her analysis of the patient's condition and risk assessment opinions in turn, and obtains the doctor's opinion. The doctor, based on his or her professional knowledge and experience, elaborates on the patient's symptoms, interpretation of the examination results, possible diagnosis and risk assessment; and in the process of the doctor's opinion, the doctor asks questions, discusses and communicates to understand the patient's condition and different opinions; S44: After all doctors have expressed their opinions, a voting session will be held. Each doctor will assess the patient's risk of TCM encephalopathy based on his or her own judgment and choose low risk, medium risk or high risk. The voting results will be counted and the final risk assessment result will be determined according to the majority voting principle. S45: Record the consultation results during the consultation process, including the doctor's opinions, voting results and final risk assessment results; summarize the consultation results, including the patient's condition analysis, risk assessment basis and next treatment recommendations; generate a written report based on the consultation results, and feedback the written report to the patient and his / her attending physician to provide a decision-making basis for the patient's treatment and management.

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