AI-assisted Colonoscopy Report System In Improving Reporting Quality

Study Overview
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Brief Summary
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In this study, the investigators proposed a prospective study about the effectiveness of speech and image recognition-based system in improving reporting quality during colonoscopy for colonoscopy report quality in endoscopists. The participants would be divided into two groups. For the collected colonoscopy videos, group A would record their observations with the assistance of the artificial intelligence system. The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions. Group B would complete the endoscopy report without special prompts. After a period of washout period, the two groups switched, that is, group A without AI assistance and group B with AI assistance to complete the colonoscopy report. Then, the completeness of the colonoscopy report, the completeness of capturing anatomical landmarks and detected lesions, the completeness of structured description, the accuracy of lesion reporting, the time for reporting and the satisfaction with the reporting system are compared with or without AI assistance.

Official Title
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Speech and Image Recognition Based System in Improving Reporting Quality During Colonoscopy

Conditions
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Artificial Intelligence, Colonoscopy

Intervention / Treatment
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* Diagnostic Test: Artificial intelligence assistant system


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients: Male or female ≥18 years old; Able to read, understand and sign an informed consent; The investigator believes that the subjects can understand the process of the clinical study, are willing and able to complete all study procedures and follow-up visits, and cooperate with the study procedures; Patients requiring colonoscopy. Doctors: Males or females who are over 18 years old; After qualified medical education and obtaining the Physician's Practice License. Exclusion Criteria: Patients: Have drug or alcohol abuse or mental disorder in the last 5 years; Pregnant or lactating women; Patients with known multiple polyp syndrome; patients with known inflammatory bowel disease; known intestinal stenosis or space-occupying tumor; known colon obstruction or perforation; patients with a history of colorectal surgery; Patients with a previous history of allergy to pre-used spasmolysis; Unable to perform biopsy due to coagulation disorders or oral anticoagulants; High-risk diseases or other special conditions that the investigator considers the subject unsuitable for participation in the clinical trial. Doctors: 1. The researcher believes that the subjects are not suitable for participating in clinical trials.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 70 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Device Feasibility
Allocation: Randomized
Intervention Model: Crossover Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: with Artificial intelligence assistant system<br>Endoscopists would complete the colonoscopy report with the assistance of the artificial intelligence system. | Diagnostic Test: Artificial intelligence assistant system<br>* The artificial intelligence assistant system can automatically capture bowel segment images and prompt abnormal lesions based on speech recognition and deep learning.<br>|
| No Intervention: without Artificial intelligence assistant system<br>Endoscopists would complete the colonoscopy report without special prompts. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The integrity of colonoscopy report | Report integrity with or without AI-assisted. Calculation method = number of information recorded / total number of information need to record x 100% | One month | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The integrity of capturing anatomical landmarks | The integrity in captured bowel landmrak images with or without AI-assisted. Calculation method = number of anatomical landmarks in captured images / total number of anatomical landmarks x 100% | One month |