[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100616587":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":30,"locations":35,"responsibleParty":51,"collaborators":18,"id":55,"slug":56,"hasResults":57,"nctId":58,"briefTitle":59,"officialTitle":60,"acronym":61,"eligibilityCriteria":62,"healthyVolunteers":63,"sex":64,"minAge":65,"maxAge":66,"enrollmentInfo":67,"targetDuration":18,"studyType":70,"phases":71,"briefSummary":73,"conditions":74,"keywords":79,"overallStatus":85,"whyStopped":18,"lastUpdateSubmitDate":86,"lastUpdatePostDateStruct":87,"startDateStruct":90,"completionDateStruct":92,"leadSponsor":94,"locationsCount":95},{"fullName":5,"class":6},"Zhejiang University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Experimental: AI-Assisted Colonoscopy","EXPERIMENTAL","Participants will undergo a high-definition colonoscopy procedure where a real-time artificial intelligence system analyzes the video feed to assist the endoscopist in identifying and highlighting suspicious lesions.",[13],"Device: AI-Assisted Colonoscopy",{"label":15,"type":16,"description":17,"interventionNames":18},"Control: Conventional Colonoscopy","NO_INTERVENTION","Participants will undergo a standard high-definition colonoscopy procedure performed by a qualified endoscopist without the assistance of the artificial intelligence system. The AI software will not be active during these procedures.",null,[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":18},"DEVICE","AI-Assisted Colonoscopy","High-definition colonoscopy procedure with a real-time video analyzed artificial intelligence system.",[9],[26],{"name":27,"affiliation":28,"role":29},"Kefeng Ding, M.D., Ph.D.","Second Affiliated Hospital, School of Medicine, Zhejiang University","STUDY_CHAIR",[31],{"name":27,"role":32,"phone":33,"phoneExt":18,"email":34},"CONTACT","+86-13906504783","dingkefeng@zju.edu.cn",[36],{"facility":37,"status":18,"city":38,"state":39,"zip":40,"country":41,"countryCode":42,"cosmosGeoPoint":43,"geoPoint":48,"contacts":49},"The Second Affiliated Hospital, Zhejiang University School of Medicine","Hangzhou","Zhejiang","310009","China","CN",{"type":44,"coordinates":45},"Point",[46,47],120.16142,30.29365,{"lat":47,"lon":46},[50],{"name":27,"role":32,"phone":33,"phoneExt":18,"email":34},{"type":52,"investigatorFullName":53,"investigatorTitle":54,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"PRINCIPAL_INVESTIGATOR","Ding Ke-Feng","Clinical professor","100616587","efficacy-of-ai-assisted-colonoscopy-for-screening-colorectal-neoplasia-ai-coloscreen-100616587",false,"NCT07307547","Efficacy of AI-Assisted Colonoscopy for Screening Colorectal Neoplasia (AI-COLOSCREEN)","A Multi-center, Randomized, Controlled Clinical Study on the Efficacy of Artificial Intelligence-Assisted Colonoscopy in Improving the Screening of Colorectal Cancer and Precancerous Lesions.","AI-COLOSCREEN","Inclusion Criteria:\n\n1. Age between 18 and 75 years, inclusive.\n2. Scheduled for a screening, diagnostic, or surveillance colonoscopy.\n3. Able to understand the study protocol and provide written informed consent.\n\nExclusion Criteria:\n\n1. Known contraindications to colonoscopy or biopsy.\n2. Personal history of colorectal cancer, inflammatory bowel disease (IBD), or previous colorectal surgery.\n3. Known or suspected colorectal polyposis syndrome (e.g., Familial Adenomatous Polyposis - FAP).\n4. Patients with active colorectal bleeding, bowel obstruction, or toxic megacolon.\n5. Women who are pregnant, planning to become pregnant, or are breastfeeding.\n6. Participation in another interventional clinical trial within the 30 days prior to enrollment.\n7. Any other condition that, in the investigator's judgment, would make the participant unsuitable for the study.",true,"ALL","18 Years","75 Years",{"count":68,"type":69},3342,"ESTIMATED","INTERVENTIONAL",[72],"NA","This study is a multi-center, randomized controlled trial designed to evaluate whether an artificial intelligence (AI) system can assist endoscopists to improve the detection rate of colorectal adenomas and cancers during colonoscopy compared to standard colonoscopy. Early screening and diagnosis are key to reducing the burden of colorectal cancer, but current colonoscopy has limitations, including the risk of missed lesions. This trial aims to determine if AI can enhance screening quality and diagnostic accuracy.",[75,76,77,78],"Colorectal Neoplasms","Colonic Polyp","Adenoma","Colorectal Cancer",[80,81,82,83,84],"Artificial Intelligence","Colonoscopy","Colorectal Cancer Screening","Adenoma Detection Rate","Deep Learning","NOT_YET_RECRUITING","2026-02-08",{"date":88,"type":89},"2026-02-10","ACTUAL",{"date":91,"type":69},"2026-04",{"date":93,"type":69},"2028-12",{"name":5,"class":6},1]