[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100641815":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":23,"centralContacts":27,"locations":32,"responsibleParty":147,"collaborators":149,"id":163,"slug":164,"hasResults":165,"nctId":166,"briefTitle":167,"officialTitle":168,"acronym":18,"eligibilityCriteria":169,"healthyVolunteers":165,"sex":170,"minAge":171,"maxAge":18,"enrollmentInfo":172,"targetDuration":18,"studyType":175,"phases":176,"briefSummary":178,"conditions":179,"keywords":182,"overallStatus":188,"whyStopped":18,"lastUpdateSubmitDate":189,"lastUpdatePostDateStruct":190,"startDateStruct":193,"completionDateStruct":195,"leadSponsor":197,"locationsCount":198},{"fullName":5,"class":6},"Peking Union Medical College Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"AI system","EXPERIMENTAL","Patients and physicians will use the study AI system prior to and during the encounter in addition to conventional clinical workflow. Use of other generative AI tools is prohibited.",[13],"Other: AI system",{"label":15,"type":16,"description":17,"interventionNames":18},"Standard of care","NO_INTERVENTION","Patients proceed directly to the consultation room without AI interaction. The attending physician conducts the encounter per standard hospital workflow using conventional clinical resources only. Use of any generative AI tool is prohibited.",null,[20],{"type":6,"name":9,"description":21,"armGroupLabels":22,"otherNames":18},"Prior to consultation, the AI system will interact with patients to build a personalised medical profile, generate a structured clinical analysis, and recommend candidate diagnoses.\n\nDuring the encounter, the AI system will interact with and be reviewed by physicians.",[9],[24],{"name":25,"affiliation":5,"role":26},"Shuyang Zhang, MD, PhD","PRINCIPAL_INVESTIGATOR",[28],{"name":25,"role":29,"phone":30,"phoneExt":18,"email":31},"CONTACT","+86-13911667211","shuyangzhang103@163.com",[33,46,59,67,75,83,91,99,107,115,123,131,139],{"facility":5,"status":18,"city":34,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":37,"geoPoint":42,"contacts":43},"Beijing","China","CN",{"type":38,"coordinates":39},"Point",[40,41],116.39723,39.9075,{"lat":41,"lon":40},[44],{"name":45,"role":29,"phone":30,"phoneExt":18,"email":31},"Shuyang Zhang",{"facility":47,"status":18,"city":48,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":49,"geoPoint":53,"contacts":54},"Cangzhou Central Hospital","Cangzhou",{"type":38,"coordinates":50},[51,52],116.85334,38.31124,{"lat":52,"lon":51},[55],{"name":56,"role":29,"phone":57,"phoneExt":18,"email":58},"Yong Li","+86-0317-2075013","czszxyyirb@163.com",{"facility":60,"status":18,"city":61,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":62,"geoPoint":66,"contacts":18},"Changchun Sacred Heart Hospital","Changchun",{"type":38,"coordinates":63},[64,65],125.32278,43.88,{"lat":65,"lon":64},{"facility":68,"status":18,"city":69,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":70,"geoPoint":74,"contacts":18},"Dongguan People's Hospital","Dongguan",{"type":38,"coordinates":71},[72,73],113.74866,23.01797,{"lat":73,"lon":72},{"facility":76,"status":18,"city":77,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":78,"geoPoint":82,"contacts":18},"First People's Hospital of Foshan","Foshan",{"type":38,"coordinates":79},[80,81],113.13148,23.02677,{"lat":81,"lon":80},{"facility":84,"status":18,"city":85,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":86,"geoPoint":90,"contacts":18},"Guizhou Provincial People's Hospital","Guiyang",{"type":38,"coordinates":87},[88,89],106.71667,26.58333,{"lat":89,"lon":88},{"facility":92,"status":18,"city":93,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":94,"geoPoint":98,"contacts":18},"Jilin Central General Hospital","Jilin City",{"type":38,"coordinates":95},[96,97],126.5608,43.84652,{"lat":97,"lon":96},{"facility":100,"status":18,"city":101,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":102,"geoPoint":106,"contacts":18},"The First People's Hospital of Yunnan Province","Kunming",{"type":38,"coordinates":103},[104,105],102.71833,25.03889,{"lat":105,"lon":104},{"facility":108,"status":18,"city":109,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":110,"geoPoint":114,"contacts":18},"Tibet Autonomous Region People's Hospital","Lhasa",{"type":38,"coordinates":111},[112,113],91.1,29.65,{"lat":113,"lon":112},{"facility":116,"status":18,"city":117,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":118,"geoPoint":122,"contacts":18},"Tianjin Children's Hospital","Tianjin",{"type":38,"coordinates":119},[120,121],117.17667,39.14222,{"lat":121,"lon":120},{"facility":124,"status":18,"city":125,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":126,"geoPoint":130,"contacts":18},"Wuhai People's Hospital","Wuhai",{"type":38,"coordinates":127},[128,129],106.81583,39.68442,{"lat":129,"lon":128},{"facility":132,"status":18,"city":133,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":134,"geoPoint":138,"contacts":18},"Qinghai Provincial People's Hospital","Xining",{"type":38,"coordinates":135},[136,137],101.75739,36.62554,{"lat":137,"lon":136},{"facility":140,"status":18,"city":141,"state":18,"zip":18,"country":35,"countryCode":36,"cosmosGeoPoint":142,"geoPoint":146,"contacts":18},"Zhangzhou Municipal Hospital of Fujian Province","Zhangzhou",{"type":38,"coordinates":143},[144,145],117.65556,24.51333,{"lat":145,"lon":144},{"type":26,"investigatorFullName":25,"investigatorTitle":148,"investigatorAffiliation":5,"oldNameTitle":18,"oldOrganization":18},"President of PUMCH",[150,151,153,155,156,157,158,159,161],{"name":47,"class":6},{"name":152,"class":6},"Zhangzhou Municipal Hospital",{"name":68,"class":154},"OTHER_GOV",{"name":76,"class":6},{"name":108,"class":6},{"name":84,"class":6},{"name":116,"class":6},{"name":160,"class":6},"The First People's Hospital of Yunnan",{"name":162,"class":6},"Qinghai People's Hospital","100641815","ai-for-rare-disease-diagnosis-in-real-world-100641815",false,"NCT07650799","AI for Rare Disease Diagnosis in Real World","A Multicentre, Prospective, Cluster-Randomised, Parallel-Controlled Trial of a Rare-Disease Large Language Model in Real-World Clinical Settings","Patient Inclusion Criteria:\n\n* Any age. Legal guardian co-signs consent for minors or individuals lacking legal capacity.\n* Diagnostically unresolved or suspected rare disease, with at least one prior complete clinical evaluation at a secondary-level or higher institution yielding no confirmed explanatory diagnosis.\n* First presentation to the enrolling institution for the current condition, with no prior records in the institutional HIS or outpatient system.\n* No prior genetic testing related to the current condition; no results or reports available.\n* Written informed consent provided voluntarily by patient or legal guardian, with commitment and ability to complete structured follow-up.\n\nPatient Exclusion Criteria:\n\n* Confirmed diagnosis (clinical, pathological, or molecular) explaining the primary symptoms.\n* Emergency presentation, critical illness, or any condition incompatible with trial participation.\n* Neither patient nor legally authorised proxy able to complete follow-up.\n* Concurrent enrollment in another interventional study with diagnostic accuracy or genetic testing yield as a primary endpoint.\n* Prior use of another AI system has already yielded a confirmed diagnosis for the current condition.\n\nPhysician Inclusion Criteria\n\n* Licensed physician in internal medicine, neurology, pediatrics, general medicine, rare disease, or a related specialty.\n* ≥2 years of clinical practice; competent to manage rare disease patients; stratified into junior or senior tier.\n* Voluntary participation with written informed consent.\n\nPhysician Exclusion Criteria\n\n* No longer in clinical practice, or unable to fulfill required outpatient duties during the study period.\n* Unwilling to provide informed consent or to permit protocol-required collection of consultation and questionnaire data.\n* Currently enrolled in another AI-assisted clinical workflow, or expected to be unable to comply with the procedures.","ALL","0 Years",{"count":173,"type":174},1055,"ESTIMATED","INTERVENTIONAL",[177],"NA","A multicentre, prospective, cluster-randomised, parallel-controlled real-world effectiveness study evaluating whether a rare-disease diagnostic large language model can improve diagnostic quality, efficiency, and health-economic outcomes for physicians managing patients with suspected rare or diagnostically unresolved disease.",[180,181],"Rare Disorders","Rare Diseases",[183,184,185,186,187],"rare diseases","AI","LLM","diagnosis","cost-effectiveness","NOT_YET_RECRUITING","2026-06-14",{"date":191,"type":192},"2026-06-16","ACTUAL",{"date":194,"type":174},"2026-06-20",{"date":196,"type":174},"2027-12-01",{"name":5,"class":6},13]