[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"differential-diagnosis\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:differential-diagnosis":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,2,0,[8,51],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":20,"targetDuration":23,"studyType":24,"phases":4,"briefSummary":25,"conditions":26,"keywords":29,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":39,"lastUpdatePostDateStruct":40,"startDateStruct":43,"completionDateStruct":45,"leadSponsor":47,"locationsCount":50},"100629116","evaluation-of-one-shot-vision-differential-diagnosis-osvde-and-multi-step-conversational-non-inferiority-mscne-in-ai-medical-interviewing-100629116",false,"NCT07470463","Evaluation of One-Shot Vision Differential Diagnosis (OSVDE) and Multi-Step Conversational Non-Inferiority (MSCNE) in AI Medical Interviewing","AI Medical Interviewing and Diagnostic System Performance Evaluation: One-Shot Vision Differential Diagnosis (OSVDE) and Multi-Step Conversational Non-Inferiority (MSCNE) Evaluation.","OSVDE-MSCNE","Inclusion Criteria:\n\n* Active license in Dermatology, Internal Medicine, Otolaryngology, Gynecology, Orthopedics, Pediatrics, Geriatrics, Emergency Medicine, Ophthalmology, Psychiatry, Endocrinology, Family Medicine, or a closely related specialty\n* Age 18 years or older\n* Ability to complete diagnostic evaluation sessions remotely using a computer or tablet with reliable internet access\n\nExclusion Criteria:\n\n* Loss of active license in an eligible specialty\n* Inability to complete the evaluation session remotely",true,"ALL","18 Years",{"count":21,"type":22},30,"ESTIMATED","6 Months","OBSERVATIONAL","This study evaluates the diagnostic performance of a multimodal artificial intelligence (AI) system (AIMD.1) using de-identified medical images and semi-synthetic patient simulations. The study combines retrospective analysis of existing publicly available image datasets with prospective data collection from licensed clinicians who complete diagnostic evaluation tasks.\n\nIn the One-Shot Vision Differential Evaluation (OSVDE) stage, clinicians review individual de-identified medical images and generate a ranked list of potential diagnoses based solely on visual features. In the Multi-Step Conversational Non-Inferiority Evaluation (MSCNE) stage, clinicians complete diagnostic assessments using semi-synthetic patient simulations derived from de-identified medical images. Clinician performance will be compared with the AI system on the same diagnostic tasks.\n\nHuman participants consist solely of licensed clinicians who provide diagnostic responses. Medical images and simulated cases are study materials and are not considered study participants. No identifiable patient data are used, and the AI system is evaluated in an offline research environment and is not used for clinical decision-making or patient care.",[27,28],"Differential Diagnosis","Diagnostic Accuracy",[30,28,27,31,32,33,34,35,36,37],"Artificial Intelligence","Clinical Decision Support","Computer Vision","Medical Imaging","Multimodal AI","Physician Performance","Non-Inferiority","Diagnostic Reasoning","RECRUITING","2026-03-20",{"date":41,"type":42},"2026-03-25","ACTUAL",{"date":44,"type":42},"2026-03-19",{"date":46,"type":22},"2026-09-19",{"name":48,"class":49},"Magic Health Inc. (d.b.a. Nolla Health)","INDUSTRY",1,{"id":52,"slug":53,"hasResults":11,"nctId":54,"briefTitle":55,"officialTitle":56,"acronym":4,"eligibilityCriteria":57,"healthyVolunteers":11,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":58,"targetDuration":23,"studyType":24,"phases":4,"briefSummary":60,"conditions":61,"keywords":64,"overallStatus":38,"whyStopped":4,"lastUpdateSubmitDate":66,"lastUpdatePostDateStruct":67,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":5},"100564439","validation-of-scoring-systems-for-differentiating-intestinal-tuberculosis-from-crohns-disease-100564439","NCT06629194","Validation of Scoring Systems for Differentiating Intestinal Tuberculosis from Crohn's Disease","Validation of Scoring Systems for Differentiating Intestinal Tuberculosis from Crohn's Disease Utilizing Clinical, Endoscopic, and Interferon-gamma Releasing Assay in Asian Population","Inclusion Criteria:\n\n1. Patients ages 18 years or older\n2. Undergoing colonoscopy and found ileal or colonic ulcers\n3. Have ileal and\u002For colonic tissue sent for mycobacterial tests, including stain for AFB, PCR, and culture\n4. Diagnosed with either intestinal tuberculosis or Crohn's disease a. Criteria of intestinal tuberculosis diagnosis includes any of following: i. Presence of caseating granuloma on pathological examination of specimens ii. Presence of acid-fast bacilli on pathological examination of specimens iii. PCR positive for Mycobacterium tuberculosis iv. Tissue culture growing organisms consistent with Mycobacterium tuberculosis v. Negative results in i to iv but response to empirical treatment with antituberculous therapy All are required to have clinical and endoscopic response to antituberculous therapy (ATT) treatment b. Diagnosis of Crohn's disease is based on clinical, endoscopic, pathological, and\u002For radiological findings which is confirmed by clinical \\& endoscopic response to Crohn's disease treatment\n\nExclusion Criteria:\n\n1\\. Patients with ileal\u002Fcolonic ulcers caused by other diseases",{"count":59,"type":22},84,"Differentiating CD from intestinal tuberculosis (ITB) is difficult due to the low sensitivities of currently available diagnostic tests. The Asia-Pacific guideline recommends anti-tuberculous therapy (ATT) for 8-12 weeks in patients with diagnostic uncertainty due to the risk of disseminated tuberculosis if patients with ITB are misdiagnosed with CD, and are prescribed immunosuppressive therapy. However, treatment with ATT has many side effects and may delay treatment in patients with CD, and this may cause severe relapse and developing complications. Many studies found that some clinical, endoscopy, pathology, radiology, and serology findings can help to improve diagnostic accuracy in these patients. However, no single diagnostic parameter can distinguish between CD and ITB. As a result, many models were developed that include various factors and modalities, and many of those models have been reported to have high performance. However, the number of studies performed to validate those models externally was limited. Correspondingly, this study is designed to prospectively validate models that integrate more advanced parameters (e.g., IGRA, CT enterography findings) with clinical, endoscopic, or pathological findings. However, it aims mainly to evaluate the model integrating clinical, endoscopic, and serological variables since CT enterography and pathological interpretation require experienced radiologists and pathologists but they are not available in many centers.",[62,63,27],"Crohn Disease","Intestinal Tuberculosis",[65,62],"Intestinal tuberculosis","2024-10-04",{"date":68,"type":42},"2024-10-08",{"date":70,"type":42},"2024-06-09",{"date":72,"type":22},"2026-03-01",{"name":74,"class":75},"Mahidol University","OTHER"]