[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100638468":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":11,"centralContacts":20,"locations":26,"responsibleParty":45,"collaborators":49,"id":51,"slug":52,"hasResults":53,"nctId":54,"briefTitle":55,"officialTitle":56,"acronym":11,"eligibilityCriteria":57,"healthyVolunteers":53,"sex":58,"minAge":59,"maxAge":11,"enrollmentInfo":60,"targetDuration":11,"studyType":63,"phases":64,"briefSummary":66,"conditions":67,"keywords":69,"overallStatus":28,"whyStopped":11,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":79,"completionDateStruct":81,"leadSponsor":83,"locationsCount":84},{"fullName":5,"class":6},"Guangdong Provincial People's Hospital","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"AI-Assisted Multidisciplinary Team Decision-Making for Non-Small Cell Lung Cancer","EXPERIMENTAL",null,[13],"Diagnostic Test: Treat Regimen",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":11},"DIAGNOSTIC_TEST","Treat Regimen","The impact of artificial intelligence on clinicians' treatment plans",[9],[21],{"name":22,"role":23,"phone":24,"phoneExt":11,"email":25},"qing liang, Dr.","CONTACT","+86 17863321987","liangtsing99@163.com",[27],{"facility":5,"status":28,"city":29,"state":30,"zip":31,"country":32,"countryCode":33,"cosmosGeoPoint":34,"geoPoint":39,"contacts":40},"RECRUITING","Guangzhou","Guangdong","510000","China","CN",{"type":35,"coordinates":36},"Point",[37,38],113.25,23.11667,{"lat":38,"lon":37},[41],{"name":42,"role":23,"phone":43,"phoneExt":11,"email":44},"Wenzhao Zhong, Dr.","+8613609777314","13609777314@163.com",{"type":46,"investigatorFullName":47,"investigatorTitle":48,"investigatorAffiliation":5,"oldNameTitle":11,"oldOrganization":11},"SPONSOR_INVESTIGATOR","Wen-zhao ZHONG","Professor",[50],{"name":5,"class":6},"100638468","evaluating-the-efficacy-and-safety-of-ai-localization-models-in-multidisciplinary-team-care-for-nsclc-100638468",false,"NCT07626736","Evaluating the Efficacy and Safety of AI Localization Models in Multidisciplinary Team Care for NSCLC","Evaluating the Efficacy and Safety of AI Localization Models in Multidisciplinary Team Care for NSCLC: a Prospective, Controlled Clinical Trial Protocol","Inclusion Criteria:\n\n1. Age ≥ 18 years;\n2. MDT (Multidisciplinary Team) discussion deems a systemic treatment plan necessary;\n3. Complete clinical, imaging, and molecular pathological data.\n\nExclusion Criteria:\n\n1. Stage I patients;\n2. Diagnosed with a thoracic tumor other than NSCLC;\n3. Lack of detailed medical data, or missing data;","ALL","18 Years",{"count":61,"type":62},300,"ESTIMATED","INTERVENTIONAL",[65],"NA","The goal of this clinical trial is to evaluate the effectiveness and safety of a locally deployed artificial intelligence (AI) decision-support model in the multidisciplinary team (MDT) process for patients with non-small cell lung cancer (NSCLC).\n\nThe main questions it aims to answer :\n\nWhat is the level of agreement between treatment recommendations generated by the AI model and those made by a traditional MDT? How often do clinicians modify their final treatment decision after reviewing the AI model's recommendation? Researchers will compare treatment plans from the traditional MDT (Arm 1), the AI model (Arm 2), and the clinician's final decision after reviewing the AI output (Arm 3) to assess consistency, decision modification rates, and clinical efficiency.\n\nParticipants will:\n\nHave their clinical, imaging, and molecular data submitted to both the traditional MDT and the AI model for independent treatment recommendations Receive a final treatment plan determined by clinicians after reviewing both recommendations, with follow-up for safety and survival outcomes",[68],"Nonsmall Cell Lung Cancer",[70,71,72,73,74],"Non-Small Cell Lung Cancer","Multidisciplinary Team","Locally Deployed AI Model","Large Language Model","Treatment Decision-Making","2026-05-31",{"date":77,"type":78},"2026-06-04","ACTUAL",{"date":80,"type":78},"2025-12-01",{"date":82,"type":62},"2028-12-31",{"name":47,"class":6},1]