[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100547291":3},{"organization":4,"armGroups":7,"interventions":17,"overallOfficials":10,"centralContacts":23,"locations":29,"responsibleParty":49,"collaborators":10,"id":51,"slug":52,"hasResults":53,"nctId":54,"briefTitle":55,"officialTitle":56,"acronym":10,"eligibilityCriteria":57,"healthyVolunteers":53,"sex":58,"minAge":59,"maxAge":10,"enrollmentInfo":60,"targetDuration":10,"studyType":63,"phases":10,"briefSummary":64,"conditions":65,"keywords":10,"overallStatus":32,"whyStopped":10,"lastUpdateSubmitDate":67,"lastUpdatePostDateStruct":68,"startDateStruct":71,"completionDateStruct":73,"leadSponsor":75,"locationsCount":76},{"fullName":5,"class":6},"Renmin Hospital of Wuhan University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-assisted group",null,"Group with AI assistance",[13],"Device: ANDOANGEL",{"label":15,"type":10,"description":16,"interventionNames":10},"Control group","Group without AI assistance",[18],{"type":19,"name":20,"description":21,"armGroupLabels":22,"otherNames":10},"DEVICE","ANDOANGEL","Polyps were identified by endoscopists assisted by an AI system: rectangular box marks; Monitoring of ileocecal position: whether blindness was reached was displayed in the lower left corner of the interface.\n\nMirror entry and exit time monitoring: the operation time is displayed in the upper left corner of the interface.\n\nColonoscopy withdrawal speed monitoring: the relative withdrawal speed was displayed on the left side of the interface.",[9],[24],{"name":25,"role":26,"phone":27,"phoneExt":10,"email":28},"Honggang Yu, Doctor","CONTACT","18771146096","wjlnsm@163.com",[30],{"facility":31,"status":32,"city":33,"state":34,"zip":35,"country":36,"countryCode":37,"cosmosGeoPoint":38,"geoPoint":43,"contacts":44},"Renmin Hospital of Wuhan Univercity","RECRUITING","Wuhan","Hubei","430060","China","CN",{"type":39,"coordinates":40},"Point",[41,42],114.26667,30.58333,{"lat":42,"lon":41},[45],{"name":46,"role":26,"phone":47,"phoneExt":10,"email":48},"Yu Honggang, Doctor","1371281899","yuhonggang@whu.edu.cn",{"type":50,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR","100547291","artificial-intelligence-assisted-system-in-colonoscopy-100547291",false,"NCT06406062","Artificial Intelligence-assisted System in Colonoscopy","To Evaluate the Effectiveness and Safety of an Artificial Intelligence-assisted System in Colonoscopy in a Real-world Obsevational Multicenter Study","Inclusion Criteria:\n\n1. age \\> 50 years old;\n2. required diagnostic colonoscopy, screening colonoscopy, or follow-up colonoscopy;\n3. voluntarily sign informed consent;\n4. Commitment to abide by the study procedures and cooperate with the implementation of the whole process of the study.\n\nExclusion Criteria:\n\n1. have participated in other clinical trials, signed informed consent and are in the follow-up period of other clinical trials;\n2. known polyposis syndrome patients;\n3. patients with known IBD;\n4. patients considered by the investigators to be unsuitable or unable to undergo complete digestive endoscopy and related examinations;\n5. high-risk diseases or other special conditions considered by the investigator to be unsuitable for clinical trial participation.","ALL","50 Years",{"count":61,"type":62},7500,"ESTIMATED","OBSERVATIONAL","In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.\n\nThis study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.\n\nThis study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study.",[66],"Adenoma Colon Polyp","2025-04-09",{"date":69,"type":70},"2025-04-13","ACTUAL",{"date":72,"type":70},"2024-05-20",{"date":74,"type":62},"2025-12-30",{"name":5,"class":6},1]