[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100629589":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":12,"centralContacts":25,"locations":31,"responsibleParty":72,"collaborators":76,"id":81,"slug":82,"hasResults":83,"nctId":84,"briefTitle":85,"officialTitle":86,"acronym":12,"eligibilityCriteria":87,"healthyVolunteers":88,"sex":89,"minAge":12,"maxAge":12,"enrollmentInfo":90,"targetDuration":12,"studyType":93,"phases":94,"briefSummary":96,"conditions":97,"keywords":100,"overallStatus":63,"whyStopped":12,"lastUpdateSubmitDate":108,"lastUpdatePostDateStruct":109,"startDateStruct":112,"completionDateStruct":114,"leadSponsor":116,"locationsCount":117},{"fullName":5,"class":6},"Copenhagen Academy for Medical Education and Simulation","OTHER",[8,13],{"label":9,"type":10,"description":11,"interventionNames":12},"Control Group","NO_INTERVENTION","Participants in the control arm perform fetal biometry using standard manual techniques without any AI assistance.",null,{"label":14,"type":15,"description":16,"interventionNames":17},"AI intervention Group","EXPERIMENTAL","The software provides real-time \"traffic light\" or score-based feedback to validate when the correct anatomical plane (BPD, HC, AC, or FL) has been reached.",[18],"Device: AI interventional group",[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":12},"DEVICE","AI interventional group","Participants in the intervention arm perform fetal biometry with the assistance of real-time Artificial Intelligence (AI) feedback software.",[14],[26],{"name":27,"role":28,"phone":29,"phoneExt":12,"email":30},"Mary Le Ngo, Medical Doctor (MD), PhD stude","CONTACT","+45 20773779","mary.van.anh.le.ngo.01@regionh.dk",[32,51,62],{"facility":33,"status":34,"city":35,"state":36,"zip":37,"country":38,"countryCode":39,"cosmosGeoPoint":40,"geoPoint":45,"contacts":46},"Nordsjællands Hospital","NOT_YET_RECRUITING","Hillerød","Capital Region","3400","Denmark","DK",{"type":41,"coordinates":42},"Point",[43,44],12.30081,55.92791,{"lat":44,"lon":43},[47],{"name":48,"role":28,"phone":49,"phoneExt":12,"email":50},"Gitte Hedermann, Associate Professor","+2520773779","gitte.hedermann.christensen@regionh.dk",{"facility":52,"status":53,"city":54,"state":55,"zip":56,"country":38,"countryCode":39,"cosmosGeoPoint":57,"geoPoint":61,"contacts":12},"Rigshospitalet","ENROLLING_BY_INVITATION","Copenhagen","København Ø","2100",{"type":41,"coordinates":58},[59,60],12.56553,55.67594,{"lat":60,"lon":59},{"facility":52,"status":63,"city":54,"state":55,"zip":56,"country":38,"countryCode":39,"cosmosGeoPoint":64,"geoPoint":66,"contacts":67},"RECRUITING",{"type":41,"coordinates":65},[59,60],{"lat":60,"lon":59},[68],{"name":69,"role":28,"phone":70,"phoneExt":12,"email":71},"Martin Tolsgaard, professor,, Medical doctor, Ph.D","+4520773779","martin.groennebaek.tolsgaard@regionh.dk",{"type":73,"investigatorFullName":74,"investigatorTitle":75,"investigatorAffiliation":5,"oldNameTitle":12,"oldOrganization":12},"PRINCIPAL_INVESTIGATOR","Mary Le Ngo","MD, PhD student",[77,79],{"name":78,"class":6},"Rigshospitalet, Denmark",{"name":80,"class":6},"Slagelse Hospital","100629589","impact-of-ai-feedback-on-ultrasound-biometry-accuracy-across-the-expertise-levels-100629589",false,"NCT07476638","Impact of AI Feedback on Ultrasound Biometry Accuracy Across the Expertise Levels","Evaluating the Sensitivity to Change of AI-Feedback in Ultrasound Biometry: A Stratified Randomized Controlled Trial Across the Expertise Gradient","Clinical Target Population: Healthcare professionals and students, including but not limited to:\n\n* Medical students (doing their masters.\n* Resident physicians and Senior Consultants in Obstetrics and Gynecology.\n\nExclusion:\n\n\\- If the participants do not understand and speak either Danish or English\n\nPregnant women:\n\nInclusion Criteria:\n\n* Pre pregnancy BMI \\\u003C 40\n* Singelton pregnancy\n* GA ≥ 37+0 at time of induction\n* Intact membranes (to ensure consistent amniotic fluid index)\n\nExclusion Criteria:\n\n* Major fetal anatomical anomaly\n* Anhydramnios (DVP \\\u003C 2 cm)\n* CPR ratio \\\u003C 2.5th percentile",true,"ALL",{"count":91,"type":92},75,"ESTIMATED","INTERVENTIONAL",[95],"NA","Objective: To evaluate the impact of real-time AI feedback on fetal biometry accuracy and investigate the Expertise Reversal Effect-whether AI benefits diminish as user experience increases.\n\nDesign: A stratified randomized trial of 75 participants (25 Novices, 25 Intermediates, 25 Experts). Users are randomized 1:1 to either AI-assisted or manual measurement groups.\n\nOutcomes:\n\n* Primary: EFW accuracy (MAPE) compared to actual birthweight.\n* Secondary: Procedure time, image quality, error relative to baseline scans, and cognitive workload (NASA-TLX).",[98,99],"Fetal Growth Abnormalities","Fetal Weight",[101,102,103,104,105,106,107],"Artificifial Intelligence feedback","Fetal weight estimation","Expertise reversal effect","Cognitive load","Explainable AI","Ultrasound","third trimester","2026-08-04",{"date":110,"type":111},"2026-08-06","ACTUAL",{"date":113,"type":111},"2026-03-01",{"date":115,"type":92},"2027-03-01",{"name":5,"class":6},3]