An artificial intelligence-based real-time evaluation and whole-process management system for bowel preparation quality
The AI-based real-time bowel preparation quality assessment system utilizes excrement sensors and deep learning models to score cleanliness and provide real-time alerts, addressing the issues of poor patient compliance and weak management of high-risk groups in traditional bowel preparation methods, thereby improving examination effectiveness and safety.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- THE FOURTH AFFILIATED HOSPITAL OF ZHEJIANG UNIV SCHOOL OF MEDICINE
- Filing Date
- 2026-01-21
- Publication Date
- 2026-05-29
AI Technical Summary
Current bowel preparation methods suffer from poor patient compliance, lack of real-time feedback, weak management of high-risk groups, and heavy workload for medical staff, resulting in insufficient bowel cleaning and affecting examination results and safety.
We employ an AI-based real-time assessment and end-to-end management system for gut health, which collects multi-dimensional data through excrement sensors, uses a deep learning model to score cleanliness, enables real-time alerts and interventions, and provides personalized guidance and data archiving.
It improved patient compliance and preparation effectiveness, reduced the risk of adverse events, enhanced examination safety and medical quality, and optimized resource allocation and treatment processes.
Smart Images
Figure CN122117361A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of medical assessment technology, and in particular to an artificial intelligence-based real-time assessment and end-to-end management system for bowel preparation quality. Background Technology
[0002] Bowel preparation is a crucial step before colonoscopy or other procedures, and its quality directly impacts the effectiveness and safety of the treatment. Currently, clinical practice mainly relies on healthcare professionals verbally or in writing informing patients of the preparation plan, which patients then perform at home. This traditional model has the following prominent problems: Patient compliance and execution deviations: Patients may fail to strictly follow the preparation requirements due to inaccurate understanding, forgetfulness, or difficulty in operation, resulting in insufficient bowel cleaning, which affects the examination field and diagnostic accuracy.
[0003] Lack of real-time feedback and assessment: Medical staff cannot keep track of the patient's progress and cleanliness status in real time during the preparation process. They can only conduct post-operative assessments during the colonoscopy. Poor preparation may lead to examination failure or the need for re-preparation, increasing medical costs and the burden on patients.
[0004] Inadequate management of high-risk groups: Elderly individuals, those with diabetes, and those with chronic constipation are considered high-risk groups for bowel preparation, which is challenging and has a high incidence of adverse reactions. Existing methods struggle to provide targeted dynamic monitoring and timely intervention, easily leading to adverse events such as falls, dehydration, and electrolyte imbalances.
[0005] Low efficiency in information transmission and communication: Limited communication channels between medical staff and patients, and delayed problem consultation and guidance, affect the continuity and safety of the preparation process.
[0006] Weak data management and research support: Data on the bowel preparation process is scattered, difficult to collect and analyze systematically, and lacks structured archives and visual reports, which is not conducive to quality control, efficacy evaluation and clinical research.
[0007] In recent years, although some mobile-based bowel preparation reminder tools have emerged, their functions are mostly limited to one-way information push and simple reminders, lacking intelligent assessment, multimodal data fusion, real-time risk warning, and doctor-patient collaborative management capabilities. In particular, there is currently no mature and systematic solution for using artificial intelligence technology to conduct real-time analysis and quality scoring of multi-dimensional data such as excrement characteristics, color, and quantity. Summary of the Invention
[0008] In view of this, the present invention provides an artificial intelligence-based real-time assessment and end-to-end management system for gut preparation quality to solve the above problems.
[0009] This invention provides an AI-based real-time assessment and end-to-end management system for bowel preparation quality, comprising: a patient terminal and a healthcare terminal, with a communication connection between the patient terminal and the healthcare terminal; the patient terminal provides functions such as setting the bowel preparation start time, selecting laxative types, viewing the examination process, querying diet and precautions, and interacting with healthcare personnel online; the healthcare terminal provides management functions such as patient management, monitoring patient preparation progress and cleanliness scores, viewing and handling early warning events, data export, and message interaction with patients, including an intelligent data acquisition module, an AI dynamic scoring module, an active early warning and intervention module, and a medical test result closed-loop verification module; wherein, the intelligent data acquisition module is used for... The system collects multi-dimensional data of excrement from patients via excrement sensors. The AI dynamic scoring module analyzes and calculates this multi-dimensional data using a built-in deep learning-based evaluation model, generating a pre-score for bowel preparation cleanliness and determining the quality level of bowel preparation based on a preset threshold. The proactive warning and intervention module analyzes the multi-dimensional data in real time, issuing warnings and providing intervention suggestions based on the analysis results. The medical examination result closed-loop verification module receives the bowel preparation cleanliness score entered by medical staff after colonoscopy, compares and statistically analyzes the pre-score and the actual cleanliness score, and calibrates and optimizes the model based on the comparison and analysis results.
[0010] Optionally, the patient terminal is also used to collect the patient's basic physical condition, including age information, disease information, medication information, diet information, and intestinal information.
[0011] Optionally, the patient terminal includes an identification and early warning module for identifying patients at high risk of falling and issuing early warnings, requiring family members to accompany such patients throughout the course of taking laxatives, thereby reducing the occurrence of adverse events caused by oral laxatives.
[0012] Optionally, the multidimensional data includes odor component indices, physical parameters, color spectral data, and estimates detected quantitatively or qualitatively by sensors.
[0013] Optionally, the active early warning and intervention module includes: a bloody stool risk identification unit, used to identify suspected blood components in excrement through image recognition and sensor data analysis, and to trigger a level one alarm to notify preset medical personnel when the proportion of blood component characteristics exceeds a preset risk threshold.
[0014] Optionally, the proactive early warning and intervention module further includes: a preparation difficulty identification unit, which uses image recognition and trait analysis algorithms to detect undissolved hard lumps, fecal stones, or excessively hard fecal residue in excrement. When hard lumps are identified, the patient is determined to be a high-risk group for intestinal preparation, triggering a secondary alarm, and intelligently generating personalized intervention suggestions based on a preset clinical rule base.
[0015] Optionally, it also includes: a data archiving and report generation module: used to automatically archive the entire preparation data of each patient to form a complete electronic record.
[0016] Another aspect of the present invention provides a method for real-time assessment and full-process management of bowel preparation quality based on artificial intelligence, including: providing interactive functions such as setting the bowel preparation start time, selecting laxative types, viewing the examination process, querying diet and precautions, and online consultation with medical staff through the patient's end; and providing management functions such as patient management, monitoring of patient preparation progress and cleanliness scores, viewing and handling of early warning events, data export, and message interaction with patients through the medical staff's end, including an intelligent data acquisition module, an artificial intelligence dynamic scoring module, an active early warning and intervention module, and a medical examination result closed-loop verification module; wherein, the intelligent data acquisition module is used to connect excrement sensors with... The system collects multi-dimensional data on excrement from the patient. The AI-powered dynamic scoring module analyzes and calculates this multi-dimensional data using a built-in deep learning-based evaluation model, generating a pre-score for bowel preparation cleanliness and determining the quality level of bowel preparation based on a preset threshold. The proactive warning and intervention module analyzes the multi-dimensional data in real time, issuing warnings and providing intervention suggestions based on the analysis results. The medical examination result closed-loop verification module receives the bowel preparation cleanliness score entered by medical staff after colonoscopy, compares and statistically analyzes the pre-score and the actual cleanliness score, and calibrates and optimizes the model based on the comparison and analysis results.
[0017] In another aspect, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of an artificial intelligence-based real-time assessment and end-to-end management system for intestinal preparation quality as described in any of the preceding claims. In another aspect, the present invention provides a computer storage medium storing a computer program that, when executed by a processor, implements the steps in an artificial intelligence-based real-time assessment and end-to-end management system for intestinal preparation quality as described in any of the preceding claims.
[0018] This invention provides a real-time assessment and end-to-end management system for bowel preparation quality based on artificial intelligence. Through the patient's end, it offers standardized and personalized guidance and intelligent reminders throughout the process, significantly improving patient understanding and adherence, thus ensuring effective preparation from the outset. Simultaneously, the system can perform risk assessments based on the patient's basic health status, issuing warnings to high-risk individuals and prompting family members to accompany them. It also analyzes excrement characteristics, proactively alerting to abnormalities such as rectal bleeding and fecal impaction, effectively enhancing the safety of the preparation process and reducing the risk of adverse events. The system enables efficient management of patient preparation progress, changes in cleanliness scores, and warning status through the healthcare provider's end. This invention effectively solves the problems of poor patient adherence, lack of real-time feedback, weak management of high-risk individuals, and heavy workload for healthcare professionals in traditional bowel preparation models. It has significant comprehensive benefits in improving medical quality and safety, optimizing resource allocation, and promoting the standardization and intelligentization of treatment processes. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. By reading the detailed description of the embodiments below, the advantages and benefits of the solutions will become clear to those skilled in the art. The accompanying drawings are only for illustrating preferred embodiments and are not intended to limit the present invention. In the accompanying drawings: Figure 1 This is a structural block diagram of the artificial intelligence-based real-time assessment and end-to-end management system for gut preparation quality, as described in an embodiment of the present invention.
[0020] Figure 2 This is a schematic diagram of the login main interface of the AI-based real-time assessment and full-process management system for gut health preparation, as described in an embodiment of the present invention.
[0021] Figure 3 This is a schematic diagram of the patient-side page of the AI-based real-time assessment and end-to-end management system for bowel preparation quality, as described in an embodiment of the present invention.
[0022] Figure 4a This is a schematic diagram of the healthcare client page of the AI-based real-time assessment and end-to-end management system for gut health preparation quality, as described in an embodiment of the present invention.
[0023] Figure 4b This is a schematic diagram of the healthcare client page of the AI-based real-time assessment and end-to-end management system for gut health preparation quality, as described in an embodiment of the present invention. Detailed Implementation
[0024] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art should fall within the protection scope of the present invention.
[0025] See Figure 1 This invention provides an artificial intelligence-based real-time assessment and end-to-end management system for gut health preparation, comprising: Patient terminal, medical staff terminal, and communication connection between the patient terminal and the medical staff terminal; The patient-side interface provides interactive functions such as setting the start time of bowel preparation, selecting the type of laxative, viewing the examination process, querying diet and precautions, and consulting with medical staff online. The healthcare terminal provides management functions such as patient management, monitoring of patient preparation progress and cleanliness scores, viewing and handling of early warning events, data export, and message interaction with patients. It includes an intelligent data acquisition module, an artificial intelligence dynamic scoring module, an active early warning and intervention module, and a medical test result closed-loop verification module. The intelligent data acquisition module is used to collect multi-dimensional data of excrement through the excrement sensor and the patient terminal; The AI dynamic scoring module is used to analyze and calculate the multi-dimensional data through a built-in deep learning-based evaluation model, generate a pre-score for bowel preparation cleanliness, and determine the quality level of bowel preparation based on a preset threshold. The proactive early warning and intervention module is used to analyze the multi-dimensional data in real time, issue early warnings based on the analysis results, and provide intervention suggestions. The medical examination result closed-loop verification module is used to receive the bowel preparation cleanliness score entered by medical staff after colonoscopy, correlate and compare the cleanliness pre-score with the cleanliness score and perform statistical analysis, and calibrate and optimize the model based on the comparison and analysis results.
[0026] Optionally, the patient terminal is also used to collect the patient's basic physical condition, including age information, disease information, medication information, diet information, and intestinal information.
[0027] Optionally, the patient terminal includes an identification and early warning module for identifying patients at high risk of falling and issuing early warnings, requiring family members to accompany such patients throughout the course of taking laxatives, thereby reducing the occurrence of adverse events caused by oral laxatives.
[0028] Optionally, the multidimensional data includes odor component indices, physical parameters, color spectral data, and estimates detected quantitatively or qualitatively by sensors.
[0029] Optionally, the active early warning and intervention module includes: a bloody stool risk identification unit, used to identify suspected blood components in excrement through image recognition and sensor data analysis, and to trigger a level one alarm to notify preset medical personnel when the proportion of blood component characteristics exceeds a preset risk threshold.
[0030] Optionally, the proactive early warning and intervention module further includes: a preparation difficulty identification unit, which uses image recognition and trait analysis algorithms to detect undissolved hard lumps, fecal stones, or excessively hard fecal residue in excrement. When hard lumps are identified, the patient is determined to be a high-risk group for intestinal preparation, triggering a secondary alarm, and intelligently generating personalized intervention suggestions based on a preset clinical rule base.
[0031] Optionally, it also includes: a data archiving and report generation module: used to automatically archive the entire preparation data of each patient to form a complete electronic record.
[0032] An exemplary embodiment of the present invention also provides a method for real-time assessment and full-process management of gut health preparation quality based on artificial intelligence, including: The patient-facing interface provides interactive functions such as setting the start time for bowel preparation, selecting the type of laxative, viewing the examination process, querying diet and precautions, and consulting with medical staff online. The medical staff terminal provides management functions such as patient management, monitoring of patient preparation progress and cleanliness scores, viewing and handling of early warning events, data export, and message interaction with patients. It includes intelligent data collection module, artificial intelligence dynamic scoring module, proactive early warning and intervention module, and medical test result closed-loop verification module. The intelligent data acquisition module is used to collect multi-dimensional data of excrement through the excrement sensor and the patient terminal; The AI dynamic scoring module is used to analyze and calculate the multi-dimensional data through a built-in deep learning-based evaluation model, generate a pre-score for bowel preparation cleanliness, and determine the quality level of bowel preparation based on a preset threshold. The proactive early warning and intervention module is used to analyze the multi-dimensional data in real time, issue early warnings based on the analysis results, and provide intervention suggestions. The medical examination result closed-loop verification module is used to receive the bowel preparation cleanliness score entered by medical staff after colonoscopy, correlate and compare the cleanliness pre-score with the cleanliness score and perform statistical analysis, and calibrate and optimize the model based on the comparison and analysis results.
[0033] Furthermore, the solution of the present invention is further described with reference to the following examples: This invention system is developed using the HTML language, which offers significant cross-platform advantages, compatible with PCs, Android, and iOS, thus reducing development and operational costs. Considering the specific circumstances of patients requiring bowel preparation, the patient-side design prioritizes intuitiveness and ease of use. Before development, the research team and software developers discussed and determined the application's functional components, dividing these functions into specific modules according to actual needs. After completing the above steps, the software developers listed all system functions, confirmed the specific functions with research team members, and presented and prepared materials using tables, documents, images, or videos. Finally, the software developers produced the software.
[0034] The initial design of the program mainly includes two ports: the patient port and the healthcare provider port. The patient port has eight sections: bowel preparation start time, types of oral laxatives, colonoscopy / treatment flowchart, pre-examination dietary recommendations, pre-examination / treatment precautions, post-examination / treatment precautions, contact for consultation, and new message viewing. The healthcare provider port has eight sections: image viewing, patient management, message viewing, data export, my team, feedback, permission application, and logout / login. See details below. Figure 2 .
[0035] See Figure 3 The system displays the patient's profile page. Upon entering the system, it automatically prompts for the collection of general patient information. Patients exhibiting one or more of the following characteristics are considered high-risk for bowel preparation: advanced age (e.g., over 75 years), diabetes, chronic constipation, history of stroke, chronic kidney disease, severe heart failure, long-term use of anticoagulants or narcotic analgesics, cognitive impairment, or a history of inadequate bowel preparation. For patients meeting these high-risk criteria, the system provides different recommendations than for the general population when administering laxatives, such as: taking the laxative two hours earlier, increasing the dosage, or changing the type of laxative.
[0036] The system identifies patients at high risk of falling and will issue a red alert for such individuals, requiring them to be accompanied by family members throughout the use of laxatives to reduce the occurrence of adverse events caused by oral laxatives.
[0037] The patient-side interface includes eight sections: bowel preparation start time, types of oral laxatives, colonoscopy / treatment flowchart, pre-examination dietary recommendations, pre-examination / treatment precautions, post-examination / treatment precautions, contact for consultation, and new messages.
[0038] After logging in with their account and password on the patient's end, patients can click on the "Breakfast Preparation Start Time" section to see six start time settings: 19:00 & 2:00; 19:00 & 7:00; 3:00; 19:00 & 3:00; 2:00; 7:00. The system will send reminders at the corresponding time after setting the desired time. Patients can select the appropriate bowel preparation start time based on their scheduled colonoscopy appointment.
[0039] Clicking on the "Types of Oral Laxatives" section will show you the types of laxatives commonly available on the market, such as Chuanbeiqing, Fujingqing, and Hengkangzhengqing. Patients can choose the corresponding medication based on the type of laxative they have.
[0040] Clicking on the "Colonoscopy / Treatment Flowchart" section allows patients to view the entire intestinal examination process.
[0041] Clicking on the "Dietary Recommendations Before Examination" section will show you recommended meals for the day before the examination and dietary recommendations for the day of the examination.
[0042] Clicking on the "Precautions before examination / treatment" section will show you precautions such as: medication and disease control, personal items, and helpful tips.
[0043] Clicking on the "Precautions after examination / treatment" section will show you dietary recommendations, symptom observation, and contraindications after colonoscopy / treatment.
[0044] Clicking on the "Consult" section allows you to communicate with medical staff on this page.
[0045] Clicking on the "View New Messages" section will show you message notifications and answers from medical staff.
[0046] See Figure 4a , Figure 4b The page for healthcare professionals was displayed, which includes eight sections: image viewing, patient management, message viewing, data export, my team, feedback, permission application, and logout.
[0047] After logging in with their account and password, healthcare staff can click on the "View Images" section. At the top of the page, they can select the patient type (outpatient / inpatient) or quickly find images of the target patient's bowel preparation by searching for their case number. The page below displays the patient's name, case number, and the patient's most recently uploaded image of bowel preparation. Clicking on an image allows for a larger view.
[0048] Clicking on the "Patient Management" section reveals a user interface at the top where they can select patient type (outpatient / inpatient) or quickly find a target patient by searching their case number. The page below displays the patient's name and case number. Clicking on the patient's name / case number allows viewing their current progress, such as oral laxative stage, exercise stage, bowel preparation completed, colonoscopy in progress, or colonoscopy completed. After the colonoscopy is complete, healthcare professionals can upload the patient's Boston score on this page. A dialog box to the right of the name / case number field allows healthcare professionals to interact with and guide the patient.
[0049] Clicking on the "Message Viewing" section allows medical staff to view patient messages through this portal.
[0050] Clicking on the "Data Export" section allows medical staff to export patient data, such as basic information like patient height, weight, case number, and medical history (the required information can be set according to the needs of medical staff, and the data can be exported after the patient fills it in).
[0051] Clicking on the "My Team" section allows healthcare workers to communicate with other healthcare professionals.
[0052] You can click on the "Feedback" section to report any problems with the software.
[0053] Clicking on the "Permission Request" section allows you to apply for permission to export patient data. Only healthcare professionals who have successfully applied can download the corresponding patient data.
[0054] Clicking the "Logout" section allows you to change your logout method and update your personal information.
[0055] The system is also equipped with an intelligent data acquisition module, which, through a dedicated excrement sensor and a patient-side mobile application, allows patients or medical staff to collect multi-dimensional data on excrement during the bowel preparation process via a smart terminal. The data includes odor component indices, physical parameters, color spectral data, and estimated quantities, quantitatively or qualitatively detected by the sensors; simultaneously, patients can upload standard-compliant digital images of their excrement.
[0056] The AI-powered dynamic scoring module incorporates a deep learning-based evaluation model (such as Convolutional Neural Networks (CNNs) for image analysis, and temporal models or fusion networks for multi-source data). This model performs real-time, comprehensive analysis of uploaded odor, characteristics, color, quantity, and image features, automatically calculating a comprehensive pre-score for bowel preparation cleanliness. A defined quality threshold (e.g., score ≥90%) is set to determine whether bowel preparation quality has reached the "excellent" level, providing patients and healthcare professionals with intuitive and quantifiable feedback on preparation progress.
[0057] Proactive early warning and intervention module: The rectal bleeding risk identification unit is used for early warning of potential rectal bleeding risks: the system uses image recognition and sensor data analysis to specifically identify suspected blood components in excrement. When the algorithm determines that the proportion of blood component characteristics exceeds a preset risk threshold (e.g., 60%), the system immediately triggers a level one alarm. The alarm message clearly indicates "Possible rectal bleeding, please pay attention," and notifies preset medical staff or customer service personnel through message push, interface pop-ups, etc. The alarm interface provides "Confirm" and "Don't remind again" options. "Confirm" indicates that the issue has been handled and recorded by the system; selecting "Don't remind again" suspends this alarm for the current bowel preparation cycle for that patient, but the event is still recorded in the background to ensure no risk is missed while avoiding repeated interference.
[0058] The bowel preparation difficulty identification unit is used for early identification and intervention of individuals with bowel preparation difficulties. The system uses image recognition and trait analysis algorithms to detect the presence of undissolved lumps, fecal stones, or excessively hard fecal matter in the excrement. Once lumps are identified, the system determines that the patient belongs to a high-risk group for bowel preparation (i.e., high risk of inadequate preparation or poor response to laxatives), and immediately triggers a level-two alarm. Simultaneously with the alarm, the system does not simply issue a warning; instead, based on a pre-set clinical rule base, it intelligently generates preliminary personalized intervention suggestions, such as: "It is recommended to increase the amount of water consumed in divided doses by 500-1000ml in addition to the existing plan," "Consider adding one dose of a specific type of laxative," and "After assessment, a cleansing enema may need to be scheduled as supplementary preparation." Healthcare professionals can refer to these suggestions, combined with the patient's specific situation, and send formal guidance information to the patient through the system, achieving a rapid response closed loop from "risk identification" to "intervention suggestions" to "instruction issuance."
[0059] Closed-loop verification module for medical examination results: After a colonoscopy, the doctor enters the intestinal cleanliness results observed during the procedure into the system terminal and uses the internationally recognized Boston Bowel Preparation Rating Scale for authoritative scoring. The system automatically correlates, compares, and statistically analyzes the doctor's Boston score with the AI-generated pre-scoring cleanliness score. This comparison data is continuously fed back into the AI model training process to continuously calibrate and optimize the accuracy and reliability of the evaluation algorithm, forming a closed-loop learning system of "monitoring-prediction-verification-optimization".
[0060] The system of this invention also has the following functions: Full-process visual monitoring: Provides medical staff with a management cockpit view, allowing them to view the preparation progress of all patients, cleanliness score change curves, alarm events, and handling status in real time.
[0061] Data archiving and report generation: Automatically archives all preparation data for each patient (including all sensor data, images, AI scores, doctor scores, alarm records, and interventions) to form a complete electronic record. It can generate bowel preparation quality reports that meet medical quality management requirements with a single click, for use in research, quality control, or patient education.
[0062] Access control and collaboration: Supports permission allocation for different roles (doctors, nurses, patients, administrators) to ensure data security and smooth workflow.
[0063] After the application is built, perform interaction testing, functional testing, interruption testing, adaptation and compatibility testing, performance testing, stability testing, security testing, regression testing, and user experience testing.
[0064] In summary, the AI-based real-time assessment and end-to-end management system for bowel preparation quality of this invention provides standardized and personalized guidance and intelligent reminders throughout the process via the patient's end, significantly improving patient comprehension accuracy and operational compliance, thus ensuring the effectiveness of preparation from the outset. Simultaneously, the system can perform risk assessments based on the patient's basic health status, issuing warnings to high-risk individuals and prompting family members to accompany them, analyzing excrement characteristics, and proactively alerting to abnormalities such as rectal bleeding and fecal impaction, effectively improving the safety of the preparation process and reducing the risk of adverse events. The system also enables efficient management of patient preparation progress, changes in cleanliness scores, and warning status via the healthcare provider's end. This invention effectively solves the problems of poor patient compliance, lack of real-time feedback, weak management of high-risk individuals, and heavy workload for healthcare professionals in traditional bowel preparation models, demonstrating significant comprehensive benefits in improving medical quality and safety, optimizing resource allocation, and promoting the standardization and intelligentization of treatment processes.
[0065] An exemplary embodiment of the present invention also provides an electronic device, which includes: a processor, a memory, a communication bus, and a communication interface.
[0066] in: The processor, memory, and communication interface communicate with each other via a communication bus.
[0067] A communication interface is used to communicate with other electronic devices or servers.
[0068] The processor is used to execute programs, specifically, to perform any of the steps of the artificial intelligence-based real-time assessment and end-to-end management system for gut preparation quality in the above embodiments.
[0069] Specifically, the program may include program code, which includes computer operation instructions.
[0070] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.
[0071] Memory is used to store programs. Memory may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.
[0072] Specifically, the program can be used to cause the processor to execute the steps of any of the AI-based real-time assessment and end-to-end management systems / methods for gut health preparation described in the embodiments. The specific implementation of each step in the program can be found in the corresponding descriptions of the steps and units executed by any of the AI-based real-time assessment and end-to-end management systems / methods for gut health preparation described above, and will not be repeated here. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the devices and modules described above can be referred to the corresponding process descriptions in the foregoing method embodiments.
[0073] An exemplary embodiment of the present invention also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the methods of various embodiments of the present invention.
[0074] The methods described above according to embodiments of the present invention can be implemented in hardware, firmware, or as software or computer code that can be stored in a recording medium (such as a CD-ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code originally stored on a remote recording medium or a non-transitory machine-readable medium and subsequently stored on a local recording medium, downloaded via a network. Thus, the methods described herein can be processed by software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components (e.g., RAM, ROM, flash memory, etc.) capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods described herein. Furthermore, when a general-purpose computer accesses code used to implement the methods shown herein, the execution of the code transforms the general-purpose computer into a dedicated computer for executing the methods shown herein.
[0075] Specific embodiments of the present invention have now been described. Other embodiments are within the scope of the appended claims. In some cases, the actions described in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result.
[0076] It should be noted that all directional indications (such as up, down, left, right, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship between the components in a certain order (as shown in the figure). If the specific order changes, the directional indication will also change accordingly.
[0077] In the description of this invention, the terms "first" and "second" are used only for convenience in describing different components or names, and should not be construed as indicating or implying a sequential relationship, relative importance, or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first" and "second" may explicitly or implicitly include at least one of that feature.
[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
[0079] It should be noted that although specific embodiments of the present invention have been described in detail with reference to the accompanying drawings, this should not be construed as limiting the scope of protection of the present invention. Various modifications and variations that can be made by those skilled in the art without inventive effort within the scope described in the claims still fall within the scope of protection of the present invention.
[0080] The examples of the embodiments of the present invention are intended to concisely illustrate the technical features of the embodiments of the present invention, so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended to be an improper limitation of the embodiments of the present invention.
[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A real-time assessment and end-to-end management system for gut health preparation quality based on artificial intelligence, characterized in that, include: Patient terminal, medical staff terminal, and communication connection between the patient terminal and the medical staff terminal; The patient-side interface provides interactive functions such as setting the start time of bowel preparation, selecting the type of laxative, viewing the examination process, querying diet and precautions, and consulting with medical staff online. The healthcare terminal provides management functions such as patient management, monitoring of patient preparation progress and cleanliness scores, viewing and handling of early warning events, data export, and message interaction with patients. It includes an intelligent data acquisition module, an artificial intelligence dynamic scoring module, an active early warning and intervention module, and a medical test result closed-loop verification module. The intelligent data acquisition module is used to collect multi-dimensional data of excrement through the excrement sensor and the patient terminal; The AI dynamic scoring module is used to analyze and calculate the multi-dimensional data through a built-in deep learning-based evaluation model, generate a pre-score for bowel preparation cleanliness, and determine the quality level of bowel preparation based on a preset threshold. The proactive early warning and intervention module is used to analyze the multi-dimensional data in real time, issue early warnings based on the analysis results, and provide intervention suggestions. The medical examination result closed-loop verification module is used to receive the bowel preparation cleanliness score entered by medical staff after colonoscopy, correlate and compare the cleanliness pre-score with the cleanliness score and perform statistical analysis, and calibrate and optimize the model based on the comparison and analysis results.
2. The system according to claim 1, characterized in that, The patient terminal is also used to collect basic physical information about patients, including age, disease, medications taken, diet, and gut health.
3. The system according to claim 2, characterized in that, The patient terminal includes an identification and early warning module, which is used to identify patients at high risk of falling and issue early warnings, requiring family members to accompany such patients throughout the use of laxatives, thereby reducing the occurrence of adverse events caused by oral laxatives.
4. The system according to claim 1, characterized in that, The multidimensional data includes odor component indices, physical properties, color spectral data, and estimates, which are quantitatively or qualitatively detected by sensors.
5. The system according to claim 1, characterized in that, The proactive early warning and intervention module includes: The blood in stool risk identification unit is used to identify suspected blood components in excrement through image recognition and sensor data analysis. When the proportion of blood component characteristics exceeds a preset risk threshold, a level one alarm is triggered to notify the preset medical staff.
6. The system according to claim 5, characterized in that, The proactive early warning and intervention module also includes: The preparation of the difficult identification unit uses image recognition and trait analysis algorithms to detect undissolved hard lumps, fecal stones, or excessively hard fecal residue in excrement. When hard lumps are identified, the patient is determined to be a high-risk group for intestinal preparation, triggering a secondary alarm, and personalized intervention suggestions are intelligently generated based on a preset clinical rule base.
7. The system according to claim 1, characterized in that, Also includes: Data archiving and report generation module: used to automatically archive the entire preparation data of each patient to form a complete electronic record.
8. A method for real-time assessment and full-process management of gut health preparation quality based on artificial intelligence, characterized in that, include: The patient-facing interface provides interactive functions such as setting the start time for bowel preparation, selecting the type of laxative, viewing the examination process, querying diet and precautions, and consulting with medical staff online. The medical staff terminal provides management functions such as patient management, monitoring of patient preparation progress and cleanliness scores, viewing and handling of early warning events, data export, and message interaction with patients. It includes intelligent data collection module, artificial intelligence dynamic scoring module, proactive early warning and intervention module, and medical test result closed-loop verification module. The intelligent data acquisition module is used to collect multi-dimensional data of excrement through the excrement sensor and the patient terminal; The AI dynamic scoring module is used to analyze and calculate the multi-dimensional data through a built-in deep learning-based evaluation model, generate a pre-score for bowel preparation cleanliness, and determine the quality level of bowel preparation based on a preset threshold. The proactive early warning and intervention module is used to analyze the multi-dimensional data in real time, issue early warnings based on the analysis results, and provide intervention suggestions. The medical examination result closed-loop verification module is used to receive the bowel preparation cleanliness score entered by medical staff after colonoscopy, correlate and compare the cleanliness pre-score with the cleanliness score and perform statistical analysis, and calibrate and optimize the model based on the comparison and analysis results.
9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the artificial intelligence-based real-time assessment and full-process management method for intestinal preparation quality as described in claim 8.
10. A computer storage medium, characterized in that, The computer storage medium stores a computer program, which, when executed by a processor, implements the steps in the artificial intelligence-based real-time assessment and full-process management method for intestinal preparation quality as described in claim 8.