[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100655669":3},{"organization":4,"outcomesModule":7,"designInfo":13,"detailedDescription":11,"studyPopulation":14,"armGroups":11,"interventions":15,"overallOfficials":11,"centralContacts":11,"locations":11,"responsibleParty":19,"collaborators":11,"id":23,"slug":24,"hasResults":25,"nctId":26,"briefTitle":27,"officialTitle":28,"acronym":11,"eligibilityCriteria":29,"healthyVolunteers":25,"sex":30,"minAge":31,"maxAge":32,"enrollmentInfo":33,"targetDuration":36,"studyType":37,"phases":11,"briefSummary":38,"conditions":39,"keywords":11,"overallStatus":41,"whyStopped":11,"lastUpdateSubmitDate":42,"lastUpdatePostDateStruct":43,"startDateStruct":46,"completionDateStruct":48,"leadSponsor":50,"locationsCount":11},{"fullName":5,"class":6},"Shandong University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":11,"otherOutcomes":11},[9],{"measure":10,"description":11,"timeFrame":12},"Presence of colonic polyps and colorectal cancer.",null,"At the time of enrollment and colonoscopy examination",{"allocation":11,"interventionModel":11,"interventionModelDescription":11,"primaryPurpose":11,"observationalModel":6,"timePerspective":6,"maskingInfo":11},"Participants aged 18-80 years who are scheduled to undergo colonoscopy. All participants provide informed consent. This study enrolls subjects preparing for colonoscopic examination to collect multimodal data for constructing an artificial intelligence-based colorectal cancer risk assessment model.",[16],{"type":6,"name":17,"description":18,"armGroupLabels":11,"otherNames":11},"Multimodal non-invasive detection for colorectal cancer","Collection of facial images, tongue images and exhaled gas data from participants. No therapeutic intervention is performed. The collected multimodal data will be used to build an artificial intelligence-based colorectal cancer risk assessment model.",{"type":20,"investigatorFullName":21,"investigatorTitle":22,"investigatorAffiliation":5,"oldNameTitle":11,"oldOrganization":11},"SPONSOR_INVESTIGATOR","Xiuli Zuo","Professor, Chief Physician, Department of Gastroenterology","100655669","multimodal-artificial-intelligence-for-non-invasive-colorectal-cancer-screening-based-on-holographic-biology-100655669",false,"NCT07815093","Multimodal Artificial Intelligence for Non-Invasive Colorectal Cancer Screening Based on Holographic Biology","Multimodal Artificial Intelligence for Non-Invasive Colorectal Cancer Screening Based on Holographic Biology.","Inclusion Criteria:\n\n1. Patients aged 18-80 years scheduled to undergo colonoscopy.\n2. All patients provide informed consent and sign the informed consent form.\n\nExclusion Criteria:\n\n1. Patients with severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders that prevent colonoscopy;\n2. Patients with a history of gastrointestinal surgery;\n3. Patients taking bismuth agents or other staining medications.","ALL","18 Years","80 Years",{"count":34,"type":35},11000,"ESTIMATED","1 Day","OBSERVATIONAL","The purpose of this study is to propose a non-invasive screening method by integrating holographic biological theory and artificial intelligence technology. A colorectal cancer risk assessment model will be constructed by analyzing multimodal data including facial features, tongue image characteristics and exhaled gas. The hypothesis of this study is that the model can attain both sensitivity and specificity of 80%.This study will enroll patients aged 18-80 years scheduled to undergo colonoscopy. All participants shall provide informed consent and sign the informed consent form. Patients will be excluded if they have severe cardiac, cerebral, pulmonary or renal dysfunction, or psychiatric disorders precluding colonoscopy, have a history of gastrointestinal surgery, or have taken bismuth agents or other staining medications. Based on estimates from existing literature, the training set will require tongue images, facial images, exhaled gas analysis results and colonoscopic diagnoses from 5000 patients, and the test set will require such data from 6000 patients.",[40],"Colorectal Cancer","NOT_YET_RECRUITING","2026-09-06",{"date":44,"type":45},"2026-09-11","ACTUAL",{"date":47,"type":35},"2026-10-01",{"date":49,"type":35},"2028-07-01",{"name":21,"class":6}]