Inflammatory bowel disease patient report evaluation system based on artificial intelligence

Abstract

The invention discloses an inflammatory bowel disease patient report evaluation system based on artificial intelligence, and relates to the technical field of medical treatment, an age group analysis module calculates historical intestinal injury factors according to historical data of patients of different ages, analyzes the influence of different ages on intestinal injury, constructs corresponding influence coefficients, and combines blood extraction data to obtain a report evaluation result of the patients of the inflammatory bowel disease; and the activity coefficient of the current patient is obtained, so that the inflammation intensity of the patient can be more accurately judged, and the defect of a traditional evaluation method under age difference is overcome. The intestinal tract state analysis module constructs a pathological prediction model by using a deep learning technology, constructs a pathological complexity coefficient according to image data, and obtains a risk assessment coefficient by combining model fitting, and the application of deep learning can more accurately assess the pathological complexity and provide more scientific risk assessment. And the report evaluation module carries out comparative analysis on the risk evaluation coefficient through a preset evaluation threshold value, and generates complete exclusive disease reports of different grades.

Description

Technical Field

[0001] The present invention relates to the technical field of medical treatment, and in particular to an inflammatory bowel disease patient report evaluation system based on artificial intelligence. Background Art

[0002] Inflammatory bowel disease (IBD) is a group of chronic inflammatory bowel diseases, including Crohn's disease (CD) and ulcerative colitis (UC). The incidence of IBD varies worldwide, but is generally on the rise.

[0003] Incidence trends: The global incidence of IBD has been increasing over the past few decades, especially in industrialized countries and some developing countries.

[0004] Regional differences: IBD has a higher incidence in North America, Europe, Australia, and New Zealand, while in traditional regions of Asia and Africa, the incidence is relatively low. However, with the westernization of lifestyle and dietary habits, the incidence of IBD in these regions is also increasing.

[0005] In the medical field, artificial intelligence (AI) is gradually becoming an important tool to improve the efficiency of diagnosis and treatment, especially in medical image analysis, biomarker detection and personalized treatment. Specifically, AI-based disease assessment and diagnosis systems have become an indispensable part of clinical practice, among which the patient-reported assessment system for inflammatory bowel disease (IBD) is a typical application scenario. Inflammatory bowel disease is a group of chronic inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. The incidence of inflammatory bowel disease varies worldwide, but generally shows an upward trend, so further research is needed on inflammatory bowel disease.

[0006] For patients with inflammatory bowel disease of different age groups, due to the different manifestations of intestinal function damage, the existing assessment methods may have shortcomings in reporting assessments. For example, the intestinal function parameters of older patients may be more difficult to capture the severity of inflammation, while younger patients may show more obvious intestinal dysfunction, which affects the accuracy of reported assessments. This difference may affect the accuracy of disease assessments, especially when intestinal function damage becomes an important indicator for assessing inflammatory activity and disease severity. Traditional assessment methods may ignore the impact of this, making it difficult to accurately reflect the actual condition. Summary of the invention

[0007] In view of the deficiencies of the prior art, the present invention provides an inflammatory bowel disease patient report evaluation system based on artificial intelligence, which solves the problems in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: an inflammatory bowel disease patient report evaluation system based on artificial intelligence, including a matter inspection module, a data collection module, an age group analysis module, an intestinal state analysis module and a report evaluation module;

[0009] The item inspection module is used to perform biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, and summarize the examination results to obtain a preliminary exclusive symptom report;

[0010] The data collection module is used to extract features from the data information in the preliminary exclusive disease report, so as to respectively obtain relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of the current inflammatory bowel disease patient, and to construct an inflammatory bowel disease data set in combination with historical data of inflammatory bowel disease patients of different ages;

[0011] The age group analysis module is used to calculate the historical intestinal damage factor Gsyz at different age states based on the historical data of patients with inflammatory bowel disease at different ages. L , based on the historical intestinal damage factor Gsyz at different ages L , analyze the influence of different ages on intestinal damage to construct the corresponding influence coefficient Yxs, and combine the relevant blood extraction data information to obtain the activity coefficient Hyxs of the current inflammatory bowel disease patients. According to the value of the activity coefficient Hyxs, preliminarily judge the inflammation intensity of the current inflammatory bowel disease patients. If the inflammation is in an abnormal state, further analysis will be performed;

[0012] The intestinal state analysis module is used to construct a morbidity prediction model using deep learning technology, and to construct a morbidity complexity coefficient Bfxs based on relevant image data information, and to obtain a risk assessment coefficient Wpxs by fitting the trained morbidity prediction model;

[0013] The report evaluation module is used to pre-set an evaluation threshold value P, and compare and analyze the evaluation threshold value P with the risk assessment coefficient Wpxs, so as to comprehensively analyze the severity of the current inflammatory bowel disease patient's symptoms and generate a complete exclusive symptom report.

[0014] Preferably, the matters inspection module is used to perform biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, wherein the examination items of the biochemical examination include blood tests, stool tests and intestinal function, and the examination items of the imaging examination include intestinal endoscopy and intestinal ultrasound examination; the examination results obtained through biochemical examinations and imaging examinations are summarized to obtain a preliminary exclusive symptom report.

[0015] Preferably, the data collection module includes a first collection unit, a second collection unit and a third collection unit;

[0016] The first acquisition unit is used to obtain relevant individual identity data information based on the personal information registration form filled out by the current inflammatory bowel disease patient at the hospital front desk, and the relevant individual identity data information includes name, gender, age value Nz, ID number and contact information;

[0017] The second acquisition unit is used to obtain relevant intestinal function status data information, relevant blood extraction data information and relevant stool sample data of the current inflammatory bowel disease patient according to the biochemical examination content in the preliminary exclusive symptom report, wherein the relevant intestinal function status data information includes the C-reactive protein concentration Crp, alanine aminotransferase concentration Gmnd and albumin concentration Bnd in the current inflammatory bowel disease patient; the relevant blood extraction data information includes the white blood cell count Bxs; the relevant stool sample data includes the fecal calprotectin concentration Bgdz;

[0018] The third acquisition unit is used to obtain relevant image data information according to the imaging examination content in the preliminary exclusive disease report, and the relevant image data information includes the number of fistulas in the intestine Lgs and the intestinal wall thickness difference Cbhc;

[0019] The historical data of inflammatory bowel disease patients of different ages refers to the relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of each inflammatory bowel disease patient obtained according to the historical stage in the hospital.

[0020] Preferably, the age group analysis module includes a historical data analysis unit, an impact determination unit and an inflammation intensity analysis unit;

[0021] The historical data analysis unit obtains the historical intestinal damage factor Gsyz at different ages based on the relevant intestinal function status data information of each inflammatory bowel disease patient obtained in the hospital in the historical stage. L , which is obtained according to the following formula:

[0022]

[0023] Wherein, Gmnd represents the concentration of alanine aminotransferase, Crp represents the concentration of C-reactive protein, Bnd represents the concentration of albumin, and a1, a2 and a3 are all weight values.

[0024] Preferably, the impact determination unit is used to analyze the impact of different ages on intestinal damage to construct a corresponding impact coefficient Yxs, which is specifically obtained in the following manner:

[0025]

[0026] Where Nz δ Expressed as the standard deviation of age values, Gsyz Lδ Expressed as the standard deviation of the historical intestinal damage factor, Cov(Nz,Gsyz L ) is expressed as the covariance of age values ​​and historical intestinal damage factors.

[0027] Preferably, the inflammatory bowel disease patients obtained in the historical stage of the hospital are sorted according to age to obtain a patient age data column, wherein the sorting method is: sorting from small to large age; at the same time, the inflammatory bowel disease patient closest to the age value Nz of the current inflammatory bowel disease patient is matched in the patient age data column and marked as the kth inflammatory bowel disease patient, so the influence coefficient Yxs corresponding to the kth inflammatory bowel disease patient is recorded as the kth influence coefficient Yxs k ;

[0028] According to the kth influence coefficient Yxs k , match the kth pair of elements from the patient age data column, the specific element pairing content is (Yxs k ,Yx n-k+1 );

[0029] The inflammation intensity analysis unit is used to obtain the historical intestinal damage factor Gsyz according to the historical data analysis unit. L Method to obtain the intestinal damage factor Gsyz of current inflammatory bowel disease patients D , and combined with relevant blood extraction data information, the activity coefficient Hyxs of the current inflammatory bowel disease patient is obtained, which is obtained in the following way:

[0030]

[0031] Wherein, Bxs represents the white blood cell count; Yxs n-k+1 It is represented as the (n-k+1)th influence coefficient; n is the number of patients with inflammatory bowel disease of different ages in the historical stage; k is the position of the current age value Nz of the inflammatory bowel disease patient in the patient age data column; the value range of k is from 1 to U represents the first correction constant, and b1 and b2 are weight values.

[0032] Preferably, an active threshold is preset, and the intensity of inflammation of the current inflammatory bowel disease patient is preliminarily determined by comparing and analyzing the activity coefficient Hyxs with the active threshold. The specific determination content is as follows:

[0033] If the activity coefficient Hyxs exceeds the active threshold, it is preliminarily judged that the inflammation of the current inflammatory bowel disease patient is in an abnormal state, and further analysis will be performed at this time;

[0034] If the activity coefficient Hyxs does not exceed the activity threshold, it is preliminarily determined that the inflammation of the current inflammatory bowel disease patient is not in an abnormal state.

[0035] Preferably, the intestinal state analysis module includes an intestinal detection unit and a comprehensive evaluation unit;

[0036] The intestinal detection unit is used to construct the disease complexity coefficient Bfxs according to the relevant image data information and in combination with the relevant stool sample data, which is specifically obtained in the following manner:

[0037]

[0038] Wherein, Bgdz represents the fecal calprotectin concentration, Lgs represents the number of fistulas, Cbhc represents the difference in intestinal wall thickness, R represents the second correction constant, and α and β are weight values.

[0039] Preferably, the comprehensive evaluation unit is used to input the activity coefficient Hyxs and the pathological complexity coefficient Bfxs into the pathological prediction model, and after dimensionless processing, the corresponding data values ​​are mapped to the interval [0,1], and then the risk assessment coefficient Wpxs is obtained according to the following formula:

[0040]

[0041] Wherein, F1 and F2 are weight values, and H represents the third correction constant.

[0042] Preferably, the report evaluation module includes a comparison unit and a report generation unit;

[0043] The comparison unit is used to pre-set an evaluation threshold value P, wherein the evaluation threshold value P includes a first evaluation threshold value P1 and a second evaluation threshold value P2, and the first evaluation threshold value P1 is greater than the second evaluation threshold value P2. By comparing and analyzing the risk assessment coefficient Wpxs with the first evaluation threshold value P1 and the second evaluation threshold value P2, the severity of the current inflammatory bowel disease patient's symptoms is comprehensively analyzed. The specific comparison and analysis contents are as follows:

[0044] If the risk assessment coefficient Wpxs is less than the second assessment threshold P2, it means that the symptom of the current inflammatory bowel disease patient is in a normal state, and the first complete exclusive symptom report will be generated;

[0045] If the second assessment threshold value P2 ≤ the risk assessment coefficient Wpxs ≤ the first assessment threshold value P1, it indicates that the symptom of the current inflammatory bowel disease patient is in a normal state, and a second complete exclusive symptom report is generated;

[0046] If the risk assessment coefficient Wpxs> the first assessment threshold P1, it means that the symptom of the current inflammatory bowel disease patient is not in a normal state, and a third complete exclusive symptom report will be generated at this time;

[0047] The report generating unit is used to take corresponding treatment measures according to the first complete exclusive symptom report, the second complete exclusive symptom report and the third complete exclusive symptom report obtained in the comparing unit, and the specific contents are as follows:

[0048] If the first complete exclusive symptom report is generated, the inflammatory bowel disease patient will be advised to go to the hospital for regular check-ups, undergo a routine physical examination and related intestinal examinations every 3-6 months, and be provided with dietary and lifestyle guidance;

[0049] If a second complete and dedicated symptom report is generated, the dosage and type of medication for patients with IBD will be adjusted; the frequency of examinations will be increased to once every 1-3 months, and additional nutritional support will be provided to patients with IBD;

[0050] If a third complete dedicated symptom report is generated, the inflammatory bowel disease patient will be arranged for hospitalization, and if complications arise, surgical intervention will be considered.

[0051] The present invention provides an inflammatory bowel disease patient report evaluation system based on artificial intelligence, which has the following beneficial effects:

[0052] (1) is an innovative solution designed to improve the care and quality of life of IBD patients while providing valuable data to medical professionals and researchers. By using this system, the needs and experiences of IBD patients can be better understood, leading to more personalized and effective care.

[0053] (2) Through the event inspection module, patients with inflammatory bowel disease are subjected to a variety of biochemical and imaging examinations, and the results are summarized to obtain a preliminary exclusive symptom report, further ensuring a comprehensive understanding of the patient's condition. The data collection module extracts features from the data in the preliminary report, obtains relevant intestinal function status, imaging data, blood extraction data, stool sample data and individual identity information, and combines historical data to construct an inflammatory bowel disease data set. This precision data processing helps to improve the accuracy of the analysis and ensure personalized evaluation. The age group analysis module calculates the historical intestinal damage factor Gsyz based on the historical data of patients of different ages. L, and analyze the impact of different ages on intestinal damage, construct the corresponding impact coefficient Yxs, and combine the blood extraction data to obtain the current patient's activity coefficient Hyxs, so as to more accurately judge the patient's inflammation intensity and make up for the shortcomings of traditional evaluation methods under age differences. The intestinal state analysis module uses deep learning technology to construct a morbidity prediction model, and constructs the morbidity complexity coefficient Bfxs based on imaging data, and combines model fitting to obtain the risk assessment coefficient Wpxs. This deep learning application can more accurately assess the complexity of the morbidity and provide a more scientific risk assessment. The report evaluation module compares and analyzes the risk assessment coefficient Wpxs by presetting the evaluation threshold P, and generates complete and exclusive disease reports of different levels. According to the evaluation results, the system can provide corresponding governance suggestions to further ensure the pertinence and practicality of the report content. In short, through the comprehensive application of multiple modules and the in-depth application of artificial intelligence technology, the system not only improves the accuracy and personalization of symptom assessment of patients with inflammatory bowel disease, but also further enhances the scientificity and practicality of report generation, effectively supporting clinical decision-making and personalized treatment.

[0054] (2) By calculating the historical intestinal damage factor Gsyz at different ages L , which helps the system to effectively identify the intestinal damage of patients of different age groups, thereby providing data support for personalized treatment. The impact determination unit analyzes the impact of different ages on intestinal damage and constructs the corresponding impact coefficient Yxs. By calculating the standard deviation and covariance of age values ​​and historical intestinal damage factors, it can accurately evaluate the specific impact of age on intestinal damage. This scientific evaluation method can reveal the differences in intestinal damage among patients of different age groups, so as to better adjust and optimize the treatment plan. The inflammation intensity analysis unit will accurately determine the current patient's inflammation intensity based on the age group analysis results and relevant data. This analysis not only takes into account the patient's age factor, but also integrates the specific manifestations of intestinal function, which helps to determine the specific intensity of the patient's inflammation and its possible health risks. In summary, by integrating and analyzing historical data of different age groups, the system can accurately evaluate intestinal damage and inflammation intensity, thereby improving the personalized evaluation and treatment level of inflammatory bowel disease, and has a significant beneficial effect on the health management of patients.

[0055] (3) The system creates a patient age data column by sorting the inflammatory bowel disease patients obtained in the hospital's historical stages in order of age from young to old. This sorting method ensures the systematization and standardization of patient data. The system can effectively find the kth inflammatory bowel disease patient closest to the current patient's age value Nz in the data column and mark its corresponding influence coefficient Yxs. Through this precise matching process, the system can obtain the historical data most relevant to the current patient's age, thereby providing reliable benchmark data for inflammation intensity analysis.

[0056] (4) Through detailed analysis and hierarchical management of the risk assessment coefficient Wpxs, the system provides highly personalized treatment recommendations and can formulate scientific treatment plans based on the patient's specific condition. This personalized management method can effectively improve the treatment effect and the patient's quality of life. Through regular symptom assessment and report generation, doctors can monitor the patient's health status in a timely manner and make timely interventions based on actual conditions. This dynamic health monitoring and intervention capability further improves the efficiency of disease control and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a block diagram of the artificial intelligence-based inflammatory bowel disease patient report assessment system of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Inflammatory bowel disease (IBD) is a group of chronic inflammatory bowel diseases, including Crohn's disease (CD) and ulcerative colitis (UC). The incidence of IBD varies worldwide, but is generally on the rise.

[0060] The global incidence of IBD has been increasing over the past few decades, especially in industrialized countries and some developing countries. The incidence of IBD is higher in North America, Europe, Australia, and New Zealand, while it is relatively low in traditional areas of Asia and Africa. However, with the westernization of lifestyle and dietary habits, the incidence of IBD in these areas is also increasing. North America has one of the highest incidences of IBD, with an estimated 10 to 15 new cases per 100,000 people in the United States each year. The incidence of IBD in Europe is similar to that in North America, and even higher in some areas. The incidence of IBD in Asia is lower, but has been on the rise in recent years, especially in more urbanized areas.

[0062] Genetic factors play an important role in the development of IBD. Environmental factors, including dietary habits, smoking, antibiotic use, and environmental pollution, may be associated with the development of IBD. Abnormal immune system reactions are also important factors in the development of IBD.

[0063] A healthy lifestyle, including a balanced diet, adequate exercise, and smoking cessation, may help reduce the risk of IBD. Medication is the mainstay of treatment for IBD, including anti-inflammatory drugs, immunosuppressants, and biologics. In some cases, surgery may be necessary, especially for patients who do not respond to medication.

[0064] The incidence of IBD is increasing worldwide, especially in industrialized and developing countries. Understanding the incidence trends and influencing factors of IBD is of great significance for the formulation of public health policies and the allocation of medical resources. At the same time, strengthening the prevention, early diagnosis and treatment of IBD is crucial to improving the quality of life of patients and reducing the medical burden.

[0065] Example 1

[0066] See also Figure 1 , the present invention provides an inflammatory bowel disease patient report evaluation system based on artificial intelligence, including a matter inspection module, a data collection module, an age group analysis module, an intestinal state analysis module and a report evaluation module;

[0067] The item inspection module is used to perform biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, and summarize the examination results to obtain a preliminary exclusive symptom report;

[0068] The data collection module is used to extract features from the data information in the preliminary exclusive disease report, so as to respectively obtain relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of the current inflammatory bowel disease patient, and to construct an inflammatory bowel disease data set in combination with historical data of inflammatory bowel disease patients of different ages;

[0069] The data collected by the data collection module include:

[0070] Patient Global Impression of Change Data on bowel function status of patients with current inflammatory bowel disease included patient electronic diaries, bowel movement frequency, and Crohn's Disease Activity Index (the Crohn's Disease Activity Index is an 8-item disease activity index consisting of 3 patient-reported and 5 physician-reported / laboratory items (physical examination and 1 laboratory parameter [hematocrit])).

[0071] Defecation count, abdominal pain numeric rating scale (NRS), defecation urgency NRS, patient global severity rating (PGRS)0 were obtained through patient electronic diaries, functional assessment of chronic illness therapy-fatigue (FACIT-fatigue), inflammatory bowel disease questionnaire, abdominal pain numeric rating scale, patient global severity rating, etc. were obtained through tablet devices;

[0072] The data collection module extracts data in a manner that is prior art and will not be described in detail here.

[0073] The age group analysis module is used to calculate the historical intestinal damage factor Gsyz at different age states based on the historical data of patients with inflammatory bowel disease at different ages. L , based on the historical intestinal damage factor Gsyz at different ages L , analyze the influence of different ages on intestinal damage to construct the corresponding influence coefficient Yxs, and combine with relevant blood extraction data information to obtain the activity coefficient Hyxs of the current inflammatory bowel disease patients. According to the value of the activity coefficient Hyxs, preliminarily judge the inflammation intensity of the current inflammatory bowel disease patients. If the inflammation of the current inflammatory bowel disease patients is in an abnormal state, further analysis will be performed;

[0074] The intestinal state analysis module is used to construct a morbidity prediction model using deep learning technology, and to construct a morbidity complexity coefficient Bfxs based on relevant image data information, and to obtain a risk assessment coefficient Wpxs by fitting the trained morbidity prediction model;

[0075] The report evaluation module is used to pre-set an evaluation threshold value P, and compare and analyze the evaluation threshold value P with the risk assessment coefficient Wpxs, so as to comprehensively analyze the severity of the current inflammatory bowel disease patient's symptoms and generate a complete exclusive symptom report.

[0076] During the operation of this system, firstly, the system conducts multi-faceted biochemical and imaging examinations on patients through the event inspection module, and summarizes these examination results into a preliminary exclusive symptom report, which provides a solid foundation for subsequent data analysis and evaluation. Secondly, the data collection module extracts features from the data in the preliminary exclusive symptom report, covering the patient's intestinal function status, imaging data, blood and stool sample data, and individual identity information, and combines the historical data of patients of different ages to construct a detailed inflammatory bowel disease data set. This process further ensures the comprehensiveness and multidimensionality of the data, and provides a basis for accurate analysis and decision-making. The introduction of the age group analysis module is a significant advantage of the system. By analyzing the historical data of patients of different age groups, the system can calculate the intestinal injury factors related to age, and further analyze the impact of age on intestinal injury, and construct the corresponding influence coefficient Yxs. Combined with the patient's blood extraction data, the system can accurately obtain the current patient's inflammatory activity coefficient Hyxs, thereby preliminarily judging its inflammatory intensity. This analysis method takes into account the impact of age on intestinal function damage, overcomes the evaluation defects caused by the traditional method of ignoring the evaluation between different age groups, and improves the reliability of the evaluation results. In addition, the intestinal status analysis module uses deep learning technology to construct the disease complexity coefficient Bfxs by processing relevant image data, and combines it with the trained disease prediction model to finally fit the patient's risk assessment coefficient Wpxs. This method not only improves the system's ability to predict complex diseases, but also further improves the accuracy of the assessment. Finally, the report evaluation module compares and analyzes the risk assessment coefficient Wpxs through the pre-set evaluation threshold P, comprehensively analyzes the severity of the current patient's symptoms, and generates a corresponding complete and exclusive symptom report. This process further ensures the clarity and operability of the evaluation results and can provide reliable support for clinical decision-making. In short, the system further improves the accuracy and efficiency of the condition assessment of patients with inflammatory bowel disease by integrating multiple functions such as biochemical examinations, data feature extraction, age group analysis, deep learning prediction and report generation, and has a wide range of clinical application value.

[0077] Example 2

[0078] Please refer to Figure 1 Specifically: the inspection module is used to conduct biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, wherein the inspection items of the biochemical examination include blood tests, stool tests and intestinal function, and the inspection items of the imaging examination include intestinal endoscopy and intestinal ultrasound; the inspection results obtained through biochemical examinations and imaging examinations are summarized to obtain a preliminary exclusive symptom report.

[0079] The data collection module includes a first collection unit, a second collection unit and a third collection unit;

[0080] The first acquisition unit is used to obtain relevant individual identity data information based on the personal information registration form filled out by the current inflammatory bowel disease patient at the hospital front desk, and the relevant individual identity data information includes name, gender, age value Nz, ID number and contact information;

[0081] Specifically, the hospital uses the electronic medical record system (EMR) or patient management system (PMS) to enter the patient's basic personal information into the system. This information includes but is not limited to: name, gender, age, ID number and contact information. The hospital will check whether the registered personal information is consistent with the information on the ID card to ensure that there is no error or false information. If the patient's information is incomplete or incorrect, the hospital staff will ask the patient to provide additional information or make corrections;

[0082] The second collection unit is used to obtain relevant intestinal function status data information, relevant blood extraction data information and relevant stool sample data of the current inflammatory bowel disease patient according to the biochemical examination content in the preliminary exclusive symptom report, wherein the relevant intestinal function status data information includes the C-reactive protein concentration Crp, the alanine aminotransferase concentration Gmnd and the albumin concentration Bnd in the current inflammatory bowel disease patient;

[0083] The relevant blood extraction data information includes white blood cell count Bxs;

[0084] The relevant stool sample data include stool calprotectin concentration Bgdz;

[0085] The third acquisition unit is used to obtain relevant image data information according to the imaging examination content in the preliminary exclusive disease report, and the relevant image data information includes the number of fistulas in the intestine Lgs and the intestinal wall thickness difference Cbhc;

[0086] And use dimensionless processing technology to perform dimensionless processing on the relevant data information in the inflammatory bowel disease data set, so that the units between the information are unified;

[0087] The historical data of inflammatory bowel disease patients of different ages refers to the relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of each inflammatory bowel disease patient obtained according to the historical stage in the hospital.

[0088] In this embodiment, through the biochemical examination and imaging examination performed by the event inspection module, the system can obtain multi-dimensional data including blood test, stool test, intestinal function test, intestinal endoscopy and intestinal ultrasound. This comprehensive data collection and aggregation makes the generation of preliminary exclusive disease reports more accurate and comprehensive, laying a solid foundation for subsequent evaluation and analysis. The data collection module systematically collects the patient's personal information, including name, gender, age, ID number and contact information, through the first acquisition unit, which ensures the accurate recording and effective tracking of each patient's individual identity information, further avoids the evaluation bias caused by incomplete or incorrect information, and improves the accuracy and reliability of the system. The second acquisition unit extracts key biochemical data from the preliminary exclusive disease report, which helps to understand the patient's physiological state in detail and supports more accurate disease activity assessment. The third acquisition unit provides detailed imaging data, which can reflect the actual pathological changes in the intestine, provide the necessary basic data for the intestinal state analysis module, and help evaluate the complexity of the disease. By integrating the historical data of patients with inflammatory bowel disease of different age groups, the system can analyze and compare the impact of different ages on intestinal function and pathological status. This method not only helps to identify the special pathological characteristics of different age groups, but also improves the accuracy of prediction and judgment of the current patient's condition, thereby enhancing the scientificity and accuracy of the report evaluation. Based on the summarized biochemical and imaging data, the system can construct a detailed symptom report, and conduct a comprehensive analysis according to the set evaluation threshold to generate a targeted exclusive symptom report. This can not only monitor the patient's condition in real time, but also formulate personalized treatment plans based on specific evaluation results, thereby improving the efficiency and effectiveness of disease management. In short, this system effectively improves the accuracy of inflammatory bowel disease patient reports through multi-faceted data collection, accurate data processing and comprehensive evaluation and analysis, provides doctors with a more reliable basis for diagnosis and treatment, and helps improve patients' treatment effects and quality of life.

[0089] Example 3

[0090] Please refer to Figure 1 ,Specifically: the age group analysis module includes a historical data analysis unit, an ,impact determination unit and an inflammation intensity analysis unit;

[0091] The historical data analysis unit obtains the historical intestinal damage factor Gsyz at different ages based on the relevant intestinal function status data information of each inflammatory bowel disease patient obtained in the hospital in the historical stage. L , which is obtained according to the following formula:

[0092]

[0093] Wherein, Gmnd represents the concentration of alanine aminotransferase, Crp represents the concentration of C-reactive protein, Bnd represents the concentration of albumin, a1, a2 and a3 are all weight values, among which 0<a1≤1, 0<a2≤1, 0<a3≤1, and a1+a2+a3=1.

[0094] The above-mentioned alanine aminotransferase concentration Gmnd can be measured by a blood analyzer, such as a fully automatic biochemical analyzer, which measures the alanine aminotransferase level in the blood by spectral analysis or electrochemical methods;

[0095] C-reactive protein concentration Crp is an acute phase response protein synthesized by the intestinal tract and belongs to the pentamer protein family. It increases rapidly when inflammation or infection occurs. The level usually rises significantly within 6 hours after the onset of inflammation and reaches a peak within 24-48 hours. It can usually be monitored and obtained by an immunoturbidimeter or a fully automatic biochemical analyzer.

[0096] The albumin concentration Bnd can be monitored and obtained by a blood analyzer, usually by colorimetry or immunoturbidimetry in a fully automatic biochemical analyzer, which can accurately measure the albumin level in the blood.

[0097] The influence determination unit is used to analyze the influence of different ages on intestinal damage to construct the corresponding influence coefficient Yxs, which is specifically obtained in the following manner:

[0098]

[0099] Where Nz δ Expressed as the standard deviation of age values, Gsyz Lδ Expressed as the standard deviation of the historical intestinal damage factor, Cov(Nz,Gsyz L ) is expressed as the covariance of age values ​​and historical intestinal damage factors.

[0100] It should be noted that: the intestinal function of adults is usually relatively stable, the production capacity of intestinal enzymes and proteins reaches its peak, the response of adults to inflammation is relatively standard, and the production and response capacity of inflammatory markers such as CRP, SAA, and white blood cell count are relatively strong. Due to the stable intestinal function, the regulation and response of adults to inflammation are relatively balanced;

[0101] However, with the increase of age, the intestine gradually shows signs of aging, the number of intestinal cells decreases, the ability of intestinal regeneration weakens, and the activity of intestinal enzymes may decrease. The inflammatory response of the elderly may show different characteristics. Due to the decline of intestinal function, the ability to produce acute phase response proteins such as CRP may decrease, resulting in a weakened intensity of the inflammatory response or atypical manifestations. In short, the intestinal function of adults is relatively stable and the inflammatory response is relatively standard; while the intestinal function of the elderly is in a state of decline, and the inflammatory response may be weak and atypical. These regularities not only affect the manifestations of clinical inflammatory diseases, but also need to be considered when formulating treatment plans. In addition, inflammatory bowel disease mainly includes Crohn's disease and ulcerative colitis, which are usually more common in young people, middle-aged people and the elderly.

[0102] In this embodiment, the historical data analysis unit can obtain the historical intestinal damage factor Gsyz at different ages by analyzing the relevant intestinal function status data of each inflammatory bowel disease patient obtained in the historical stage of the hospital. L , the calculation of this factor takes into account multiple groups of parameters, further ensuring a multi-faceted assessment of intestinal function damage, and this precise calculation can reveal the characteristics and trends of intestinal damage in different age groups, providing a solid data foundation for subsequent analysis. The impact determination unit analyzes the impact of different ages on intestinal damage based on the age value and the standard deviation and covariance of the historical intestinal damage factor. This process constructs the impact coefficient Yxs by calculating the age value and the standard deviation of the historical intestinal damage factor and its covariance. In this way, the system can identify and quantify the specific impact of age on intestinal damage, improving the personalized assessment ability of patients of different age groups. The inflammation intensity analysis unit uses the results of historical data analysis and impact determination to conduct a detailed analysis of the inflammation intensity of the current patient. Combined with the impact coefficient Yxs derived from historical data and the biochemical test results of the current patient, the system can more accurately judge the severity of inflammation. This analysis not only improves the accuracy of the assessment, but also helps doctors better understand the specific impact of different age groups on inflammatory bowel disease. By comprehensively considering the impact of different ages on intestinal damage and the results of inflammation intensity analysis, the system can provide patients with personalized treatment recommendations. Doctors can adjust treatment plans based on precise analysis results to suit the specific age-related needs of patients, thereby improving treatment outcomes and the quality of life of patients. The system converts complex age-related data and inflammation analysis results into easy-to-understand evaluation reports, providing doctors with data-driven decision support. In summary, the system not only improves the diagnostic accuracy of inflammatory bowel disease, but also optimizes treatment plans and decision support by analyzing intestinal damage and evaluating inflammation intensity in patients of different age groups.

[0103] Example 4

[0104] Please refer to Figure 1Specifically, the inflammatory bowel disease patients obtained in the historical stage of the hospital are sorted according to their ages to obtain the patient age data column, wherein the sorting method is: sorting from small to large age; at the same time, the inflammatory bowel disease patient closest to the age value Nz of the current inflammatory bowel disease patient is matched in the patient age data column, and marked as the kth inflammatory bowel disease patient, so the influence coefficient Yxs corresponding to the kth inflammatory bowel disease patient is recorded as the kth influence coefficient Yxs k ;

[0105] According to the kth influence coefficient Yxs k , match the kth pair of elements from the patient age data column, the specific element pairing content is (Yxs k ,Yx n-k+1 );

[0106] Here, the pairing process of the patient age data series shows symmetry because the pairing is done from the two ends of the sequence to the middle. This symmetry allows us to find the "pairing" element for each element. Symmetry is the property of an object that remains unchanged under certain transformations.

[0107] Example: For the data column {y1, y2, y3, y4, y5}, n=5, the first pair: (y1, y5), the second pair: (y2, y4), the third pair: (y3, y3), that is, the middle element matches itself;

[0108] The inflammation intensity analysis unit is used to obtain the historical intestinal damage factor Gsyz according to the historical data analysis unit. L Method to obtain the intestinal damage factor Gsyz of current inflammatory bowel disease patients D , and combined with relevant blood extraction data information, the activity coefficient Hyxs of the current inflammatory bowel disease patient is obtained, which is obtained in the following way:

[0109]

[0110] Wherein, Bxs represents the white blood cell count; Yxs n-k+1 It is represented as the (n-k+1)th influence coefficient; n is the number of patients with inflammatory bowel disease of different ages in the historical stage; k is the position of the current age value Nz of the inflammatory bowel disease patient in the patient age data column; the value range of k is from 1 to in is a symbol indicating “round up”; U represents the first correction constant, b1 and b2 are both weight values, wherein 0<b1≤1, 0<b2≤1, and b1+b2=1.

[0111] White blood cell count Bxs indicates the number of white blood cells in the blood, which are part of the immune system. Inflammation and infection usually lead to an increase in white blood cell count, especially an increase in neutrophils. It can usually be monitored and obtained by a blood analyzer, and detected in a fully automatic biochemical analyzer by colorimetry or immunoturbidimetry. This method can accurately measure the albumin level in the blood.

[0112] The active threshold is set in advance, and the activity coefficient Hyxs is compared and analyzed with the active threshold to preliminarily judge the inflammation intensity of the current inflammatory bowel disease patient. The specific judgment content is as follows:

[0113] If the activity coefficient Hyxs exceeds the active threshold, it is preliminarily judged that the inflammation of the current inflammatory bowel disease patient is in an abnormal state, and further analysis will be performed at this time;

[0114] If the activity coefficient Hyxs does not exceed the activity threshold, it is preliminarily determined that the inflammation of the current inflammatory bowel disease patient is not in an abnormal state.

[0115] In this embodiment, the system sorts the inflammatory bowel disease patients obtained in the historical stage of the hospital according to age, ensuring the accuracy of data analysis. In the patient age data column, the system matches the patient with the closest age value Nz to the current inflammatory bowel disease patient and marks it as the kth inflammatory bowel disease patient. In this way, the system can accurately identify the reference data close to the current patient's age, ensuring the relevance and practicality of historical data analysis. According to the kth influence coefficient Yxs, the system can match the element pairing content related to the kth patient from the patient age data column. This scientific calculation method can effectively reflect the intestinal damage of patients of different age groups and provide a solid foundation for the analysis of inflammation intensity. The inflammation intensity analysis unit calculates the activity coefficient Hyxs of the current inflammatory bowel disease patient by combining the historical intestinal damage factor and the relevant blood extraction data information, further ensuring the accurate assessment of the patient's inflammatory state, reducing the problem of inaccurate analysis of the patient's inflammatory state caused by the decline in intestinal function due to age. The pre-set active threshold can effectively distinguish whether the patient's inflammation is in an abnormal state by comparing and analyzing with Hyxs. Based on the comparison results of the activity coefficient Hyxs and the set activity threshold, the system can preliminarily judge the current inflammatory status of the patient. If the activity coefficient Hyxs exceeds the threshold, the system will conduct further analysis to promptly detect and deal with abnormal situations. This preliminary judgment can help doctors quickly screen out patients who need special attention and improve the efficiency of clinical decision-making. Through precise age matching and scientific activity coefficient assessment, the system can provide personalized treatment recommendations for each patient. This personalized assessment method not only improves the accuracy of diagnosis, but also optimizes the treatment plan, so that each patient can get the most suitable treatment, thereby improving the treatment effect and the patient's quality of life.

[0116] Through accurate analysis of historical data and dynamic evaluation of real-time data, the system provides data-driven decision support for medical personnel. This data-driven approach helps doctors better understand the patient's condition and make more accurate clinical decisions, thereby improving the patient's health management and treatment effects. In summary, through systematic age matching, influence coefficient calculation, and activity coefficient Hyxs evaluation, this system can improve the assessment accuracy and personalized treatment level of patients with inflammatory bowel disease, and provide patients with more accurate and efficient medical services.

[0117] Example 5

[0118] Please refer to Figure 1 ,Specifically: the intestinal state analysis module includes an intestinal detection unit and a comprehensive evaluation unit;

[0119] The intestinal detection unit is used to construct the disease complexity coefficient Bfxs according to the relevant image data information and in combination with the relevant stool sample data, which is specifically obtained in the following manner:

[0120]

[0121] Wherein, Bgdz represents the fecal calprotectin concentration, Lgs represents the number of fistulas, Cbhc represents the difference in intestinal wall thickness, R represents the second correction constant, and α and β are both weight values, wherein 0<α≤1, 0<β≤1, and α+β=1.

[0122] The fecal calprotectin concentration Bgdz mentioned above is a non-invasive marker for evaluating intestinal inflammation. Calprotectin is a protein released by activated leukocytes. The higher the calprotectin level, the more active the intestinal inflammation. It can usually be detected by fecal calprotectin detection instruments, such as enzyme-linked immunosorbent assay (ELISA) or fluorescent immunoassay instruments, which can quantitatively analyze the calprotectin concentration in fecal samples.

[0123] The number of fistulas, Lgs, can be monitored by imaging examinations such as magnetic resonance imaging (MRI) or computed tomography (CT);

[0124] The intestinal wall thickness difference Cbhc can be obtained by monitoring through endoscopic ultrasound (EUS) or abdominal ultrasound. EUS or abdominal ultrasound measures the thickness of the intestinal wall through high-frequency sound wave reflection. Doctors can calculate the difference by comparing the thickness of different parts.

[0125] In this embodiment, the intestinal detection unit constructs a morbidity complexity coefficient Bfxs by combining relevant imaging data information and stool sample data. The construction of this coefficient depends on multiple indicators such as fecal calprotectin concentration Bgdz, the number of fistulas Lgs, and the difference in intestinal wall thickness Cbhc. This comprehensive consideration method can reflect the complexity of the morbidity in the patient's intestine in many aspects and provide accurate quantification of the disease state. The system integrates the results of imaging examinations and stool sample analysis, and considers the impact of multiple indicators on the complexity of the morbidity. Specifically, the fecal calprotectin concentration Bgdz helps to evaluate the inflammatory response of the intestine, and the number of fistulas Lgs and the difference in intestinal wall thickness Cbhc provide structural information of the lesion. Such comprehensive information can more accurately evaluate the complexity of the patient's morbidity and assist doctors in making scientific treatment decisions. Using the results of the comprehensive evaluation, doctors can obtain detailed information about the patient's intestinal status, thereby optimizing personalized treatment plans. Long-term tracking and evaluation can also help doctors predict the development trend of the disease and improve the prognosis management effect of patients. In summary, the intestinal detection unit provides support for the intestinal status assessment of patients with inflammatory bowel disease by combining multidimensional data to construct the pathological complexity coefficient Bfxs. This method not only improves the accuracy of disease assessment, but also optimizes the treatment plan and patient prognosis monitoring capabilities.

[0126] Example 6

[0127] Please refer to Figure 1 Specifically, the comprehensive evaluation unit is used to input the activity coefficient Hyxs and the pathological complexity coefficient Bfxs into the pathological prediction model, and after dimensionless processing, the corresponding data values ​​are mapped to the interval [0,1], and then the risk assessment coefficient Wpxs is obtained according to the following formula:

[0128]

[0129] In the formula, F1 and F2 are weight values, H represents the third correction constant, where 0<F1≤1, 0<F2≤1, and F1+F2=1. The weight value can be obtained by referring to the hierarchical analysis method;

[0130] The initial model is constructed using the convolutional neural network in deep learning technology, and the initial model is trained and tested with relevant data information in the inflammatory bowel disease data set. The trained initial model is used as a state recognition model, and feature information in the state recognition model is obtained respectively. The state recognition model is trained and tested with the obtained feature information, and the trained state recognition model is used as a pathological prediction model.

[0131] The report evaluation module includes a comparison unit and a report generation unit;

[0132] The comparison unit is used to pre-set an evaluation threshold value P, wherein the evaluation threshold value P includes a first evaluation threshold value P1 and a second evaluation threshold value P2, and the first evaluation threshold value P1 is greater than the second evaluation threshold value P2. By comparing and analyzing the risk assessment coefficient Wpxs with the first evaluation threshold value P1 and the second evaluation threshold value P2, the severity of the current inflammatory bowel disease patient's symptoms is comprehensively analyzed. The specific comparison and analysis contents are as follows:

[0133] If the risk assessment coefficient Wpxs is less than the second assessment threshold P2, it means that the symptom of the current inflammatory bowel disease patient is in a normal state, and the first complete exclusive symptom report will be generated;

[0134] If the second assessment threshold value P2 ≤ the risk assessment coefficient Wpxs ≤ the first assessment threshold value P1, it indicates that the symptom of the current inflammatory bowel disease patient is in a normal state, and a second complete exclusive symptom report is generated;

[0135] If the risk assessment coefficient Wpxs> the first assessment threshold P1, it means that the symptom of the current inflammatory bowel disease patient is not in a normal state, and a third complete exclusive symptom report will be generated at this time;

[0136] The report generating unit is used to take corresponding treatment measures according to the first complete exclusive symptom report, the second complete exclusive symptom report and the third complete exclusive symptom report obtained in the comparing unit, and the specific contents are as follows:

[0137] If the first complete exclusive symptom report is generated, patients with inflammatory bowel disease will be advised to go to the hospital for regular check-ups, including routine physical examinations and related intestinal examinations every 3-6 months, such as blood tests, fecal calprotectin tests and ultrasound examinations. Diet and lifestyle guidance will be provided to patients with inflammatory bowel disease, encouraging them to maintain a low-inflammatory diet, such as a low-fat, low-sugar diet, avoid lactose or gluten, etc., as well as moderate physical exercise;

[0138] If a second complete and exclusive symptom report is generated, the drug dosage and type of the inflammatory bowel disease patient will be adjusted, such as increasing the use of immunosuppressants or biologics to strengthen the control of inflammation. At the same time, the frequency of examinations will be increased to once every 1-3 months to detect changes in the condition in a timely manner and make adjustments. In addition, additional nutritional support will be provided to inflammatory bowel disease patients, such as protein and vitamin supplements, to improve intestinal repair and overall health.

[0139] If a third complete dedicated symptom report is generated, the inflammatory bowel disease patient will be arranged for hospitalization and may require intravenous medication and nutritional support. If complications occur, such as intestinal perforation or severe stenosis, surgical intervention will be considered.

[0140] It should be noted that the hierarchical analysis method is a combination of qualitative and quantitative analysis methods. It can decompose complex problems into multiple levels. By comparing the importance of factors at each level, it can help decision makers make decisions on complex problems and determine the final decision plan. In this process, the hierarchical analysis method can be used to determine the weight values ​​of these indicators.

[0141] In this embodiment, the comprehensive assessment unit calculates the risk assessment coefficient Wpxs by inputting the activity coefficient Hyxs and the morbid complexity coefficient Bfxs into the morbid prediction model. This process makes the symptom assessment more accurate, can effectively distinguish the symptom of different severity, and provide patients with a clear basis for diagnosis. The comparison unit compares and analyzes the risk assessment coefficient Wpxs based on the preset No. 1 assessment threshold P1 and No. 2 assessment threshold P2. The system can generate three different complete exclusive symptom reports. This multi-level reporting mechanism can provide appropriate suggestions and treatment plans according to the actual condition of the patient, thereby improving the effect of personalized medical services. The report generation unit generates corresponding treatment suggestions based on different symptom reports. For patients in normal condition, regular check-ups and maintaining a healthy lifestyle are recommended. For patients with changes in their condition, suggestions for adjusting medications and increasing the frequency of examinations are provided. For patients with severe conditions, hospitalization and possible surgical intervention are recommended. This dynamic adjustment strategy can respond to changes in the condition in a timely manner and ensure that patients receive timely treatment. By providing detailed personalized treatment recommendations, such as adjusting medication dosages, increasing the frequency of examinations, and providing nutritional support, the system can optimize patient management and treatment outcomes. This refined management can not only improve the patient's condition, but also improve the patient's overall health. Through accurate risk assessment factors and multi-level symptom reports, the system can detect changes in the condition and potential risks earlier, allowing for timely intervention. This early detection and intervention capability helps avoid further deterioration of the condition and improves the patient's quality of life and prognosis. In general, the system can further improve the management of patients with inflammatory bowel disease, optimize treatment plans, and provide timely intervention when the condition changes, thereby improving patients' health and quality of life through accurate symptom assessments and dynamically adjusted treatment strategies.

[0142] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence-based patient-reported assessment system for inflammatory bowel disease, characterized by: It includes item inspection module, data collection module, age group analysis module, intestinal status analysis module and report evaluation module; The item inspection module is used to perform biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, and summarize the examination results to obtain a preliminary exclusive symptom report; The data collection module is used to extract features from the data information in the preliminary exclusive disease report, so as to respectively obtain relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of the current inflammatory bowel disease patient, and combine the historical data of inflammatory bowel disease patients of different ages; The age group analysis module is used to calculate the historical intestinal damage factor Gsyz at different age states based on the historical data of patients with inflammatory bowel disease at different ages. L , based on the historical intestinal damage factor Gsyz at different ages L , analyze the influence of different ages on intestinal damage to construct the corresponding influence coefficient Yxs, and combine with relevant blood extraction data information to obtain the activity coefficient Hyxs of the current inflammatory bowel disease patients. According to the value of the activity coefficient Hyxs, preliminarily judge the inflammation intensity of the current inflammatory bowel disease patients. If the inflammation of the current inflammatory bowel disease patients is in an abnormal state, further analysis will be performed; The intestinal state analysis module is used to construct a morbidity prediction model using deep learning technology, and to construct a morbidity complexity coefficient Bfxs based on relevant image data information, and to obtain a risk assessment coefficient Wpxs by fitting the trained morbidity prediction model; The report evaluation module is used to pre-set an evaluation threshold value P, and compare and analyze the evaluation threshold value P with the risk assessment coefficient Wpxs, so as to comprehensively analyze the severity of the current inflammatory bowel disease patient's symptoms and generate a complete exclusive symptom report.

2. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 1, characterized in that: The item inspection module is used to perform biochemical examinations and imaging examinations on patients with inflammatory bowel disease in advance, wherein the inspection items of the biochemical examination include blood tests, stool tests and intestinal function, and the inspection items of the imaging examination include intestinal endoscopy and intestinal ultrasound examination; the inspection results obtained through biochemical examinations and imaging examinations are summarized to obtain a preliminary exclusive symptom report.

3. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 1, characterized in that: The data collection module includes a first collection unit, a second collection unit and a third collection unit; The first acquisition unit is used to obtain relevant individual identity data information based on the personal information registration form filled out by the current inflammatory bowel disease patient at the hospital front desk, and the relevant individual identity data information includes name, gender, age value Nz, ID number and contact information; The second collection unit is used to obtain relevant intestinal function status data information, relevant blood extraction data information and relevant stool sample data of the current inflammatory bowel disease patient according to the biochemical examination content in the preliminary exclusive symptom report, wherein the relevant intestinal function status data information includes the C-reactive protein concentration Crp, alanine aminotransferase concentration Gmnd and albumin concentration Bnd in the current inflammatory bowel disease patient; the relevant blood extraction data information includes the white blood cell count Bxs; the relevant stool sample data includes the fecal calprotectin concentration Bgdz; The third acquisition unit is used to obtain relevant image data information according to the imaging examination content in the preliminary exclusive disease report, and the relevant image data information includes the number of fistulas in the intestine Lgs and the intestinal wall thickness difference Cbhc; The historical data of inflammatory bowel disease patients of different ages refers to the relevant intestinal function status data information, relevant imaging data information, relevant blood extraction data information, relevant stool sample data and relevant individual identity data information of each inflammatory bowel disease patient obtained according to the historical stage in the hospital.

4. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 3, characterized in that: The age group analysis module includes a historical data analysis unit, an impact determination unit and an inflammation intensity analysis unit; The historical data analysis unit obtains the historical intestinal damage factor Gsyz at different ages based on the relevant intestinal function status data information of each inflammatory bowel disease patient obtained in the hospital in the historical stage. L , which is obtained according to the following formula: Wherein, Gmnd represents the concentration of alanine aminotransferase, Crp represents the concentration of C-reactive protein, Bnd represents the concentration of albumin, and a1, a2 and a3 are all weight values.

5. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 4, characterized in that: The influence determination unit is used to analyze the influence of different ages on intestinal damage to construct the corresponding influence coefficient Yxs, which is specifically obtained in the following manner: Where Nz δ Expressed as the standard deviation of age values, Gsyz Lδ Expressed as the standard deviation of the historical intestinal damage factor, Cov(Nz,Gsyz L ) is expressed as the covariance of age values ​​and historical intestinal damage factors.

6. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 5, characterized in that: The inflammatory bowel disease patients obtained in the historical stage of the hospital are sorted by age to obtain the patient age data column, where the sorting method is: sorting from small to large age; at the same time, the inflammatory bowel disease patient closest to the age value Nz of the current inflammatory bowel disease patient is matched in the patient age data column and marked as the kth inflammatory bowel disease patient, so the influence coefficient Yxs corresponding to the kth inflammatory bowel disease patient is recorded as the kth influence coefficient Yxs k ; According to the kth influence coefficient Yxs k , match the kth pair of elements from the patient age data column, the specific element pairing content is (Yxs k ,Yx n-k+1 ); The inflammation intensity analysis unit is used to obtain the historical intestinal damage factor Gsyz according to the historical data analysis unit. L Method to obtain the intestinal damage factor Gsyz of current inflammatory bowel disease patients D , and combined with relevant blood extraction data information, the activity coefficient Hyxs of the current inflammatory bowel disease patient is obtained, which is obtained in the following way: Wherein, Bxs represents the white blood cell count; Yxs n-k+1 It is represented as the (n-k+1)th influence coefficient; n is the number of patients with inflammatory bowel disease of different ages in the historical stage; k is the position of the current age value Nz of the inflammatory bowel disease patient in the patient age data column; the value range of k is from 1 to U represents the first correction constant, and b1 and b2 are weight values.

7. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 6, characterized in that: The active threshold is set in advance, and the activity coefficient Hyxs is compared and analyzed with the active threshold to preliminarily judge the inflammation intensity of the current inflammatory bowel disease patient. The specific judgment content is as follows: If the activity coefficient Hyxs exceeds the active threshold, it is preliminarily judged that the inflammation of the current inflammatory bowel disease patient is in an abnormal state, and further analysis will be performed at this time; If the activity coefficient Hyxs does not exceed the activity threshold, it is preliminarily determined that the inflammation of the current inflammatory bowel disease patient is not in an abnormal state.

8. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 3, characterized in that: The intestinal state analysis module includes an intestinal detection unit and a comprehensive evaluation unit; The intestinal detection unit is used to construct the pathological complexity coefficient Bfxs according to the relevant image data information and in combination with the relevant stool sample data, which is specifically obtained in the following manner: Wherein, Bgdz represents the fecal calprotectin concentration, Lgs represents the number of fistulas, Cbhc represents the difference in intestinal wall thickness, R represents the second correction constant, and α and β are weight values.

9. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 8, characterized in that: The comprehensive evaluation unit is used to input the activity coefficient Hyxs and the pathological complexity coefficient Bfxs into the pathological prediction model, and after dimensionless processing, the corresponding data values ​​are mapped to the interval [0,1], and then the risk assessment coefficient Wpxs is obtained according to the following formula: Wherein, F1 and F2 are weight values, and H represents the third correction constant.

10. The artificial intelligence-based inflammatory bowel disease patient-reported assessment system according to claim 1, characterized in that: The report evaluation module includes a comparison unit and a report generation unit; The comparison unit is used to pre-set an evaluation threshold value P, wherein the evaluation threshold value P includes a first evaluation threshold value P1 and a second evaluation threshold value P2, and the first evaluation threshold value P1 is greater than the second evaluation threshold value P2. By comparing and analyzing the risk assessment coefficient Wpxs with the first evaluation threshold value P1 and the second evaluation threshold value P2, the severity of the current inflammatory bowel disease patient's symptoms is comprehensively analyzed. The specific comparison and analysis contents are as follows: If the risk assessment coefficient Wpxs is less than the second assessment threshold P2, it means that the symptom of the current inflammatory bowel disease patient is in a normal state, and the first complete exclusive symptom report will be generated; If the second assessment threshold value P2 ≤ the risk assessment coefficient Wpxs ≤ the first assessment threshold value P1, it indicates that the symptom of the current inflammatory bowel disease patient is in a normal state, and a second complete exclusive symptom report is generated; If the risk assessment coefficient Wpxs> the first assessment threshold P1, it means that the symptom of the current inflammatory bowel disease patient is not in a normal state, and a third complete exclusive symptom report will be generated at this time; The report generating unit is used to take corresponding treatment measures according to the first complete exclusive symptom report, the second complete exclusive symptom report and the third complete exclusive symptom report obtained in the comparing unit, and the specific contents are as follows: If the first complete exclusive symptom report is generated, the inflammatory bowel disease patient will be advised to go to the hospital for regular check-ups, undergo a routine physical examination and related intestinal examinations every 3-6 months, and be provided with dietary and lifestyle guidance; If a second complete and dedicated symptom report is generated, the dosage and type of medication for patients with IBD will be adjusted; the frequency of examinations will be increased to once every 1-3 months, and additional nutritional support will be provided to patients with IBD; If a third complete dedicated symptom report is generated, the inflammatory bowel disease patient will be arranged for hospitalization, and if complications arise, surgical intervention will be considered.

Images