[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100641551":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":20,"centralContacts":24,"locations":30,"responsibleParty":115,"collaborators":117,"id":120,"slug":121,"hasResults":122,"nctId":123,"briefTitle":124,"officialTitle":125,"acronym":10,"eligibilityCriteria":126,"healthyVolunteers":122,"sex":127,"minAge":128,"maxAge":10,"enrollmentInfo":129,"targetDuration":10,"studyType":132,"phases":10,"briefSummary":133,"conditions":134,"keywords":10,"overallStatus":52,"whyStopped":10,"lastUpdateSubmitDate":139,"lastUpdatePostDateStruct":140,"startDateStruct":143,"completionDateStruct":145,"leadSponsor":147,"locationsCount":148},{"fullName":5,"class":6},"University of North Carolina, Chapel Hill","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Pregnant Women within One Week of Delivery",null,"Participants receive a standardized ultrasound sweep protocol and specialist-performed fetal biometry.",[13],"Diagnostic Test: AI ultrasound diagnostic tool for fetal weight estimation",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":10},"DIAGNOSTIC_TEST","AI ultrasound diagnostic tool for fetal weight estimation","Participants will undergo study-specific transabdominal ultrasound acquisition using standardized abdominal sweeps of the gravid abdomen, guided by external maternal landmarks and saved as cineloop videos. The cineloop videos will be analyzed by a locked deep-learning AI diagnostic tool to generate an estimated fetal weight. The AI-generated estimate will be compared with specialist-performed fetal biometry and actual birth weight to evaluate diagnostic accuracy. The AI output is for research evaluation only and will not direct clinical management during the study.",[9],[21],{"name":22,"affiliation":5,"role":23},"Jeffrey Stringer, MD","PRINCIPAL_INVESTIGATOR",[25],{"name":26,"role":27,"phone":28,"phoneExt":10,"email":29},"Jeffrey R Stringer, MD","CONTACT","919-962-4717","jeff_stringer@unc.edu",[31,50,69,85,100],{"facility":32,"status":33,"city":34,"state":35,"zip":36,"country":37,"countryCode":38,"cosmosGeoPoint":39,"geoPoint":44,"contacts":45},"Ochsner Health","NOT_YET_RECRUITING","New Orleans","Louisiana","70115","United States","US",{"type":40,"coordinates":41},"Point",[42,43],-90.07507,29.95465,{"lat":43,"lon":42},[46],{"name":47,"role":27,"phone":48,"phoneExt":10,"email":49},"Will Williams, MD","504-842-5574","frank.williams2@ochsner.org",{"facility":51,"status":52,"city":53,"state":54,"zip":55,"country":37,"countryCode":38,"cosmosGeoPoint":56,"geoPoint":60,"contacts":61},"University of North Carolina","RECRUITING","Chapel Hill","North Carolina","27516",{"type":40,"coordinates":57},[58,59],-79.05584,35.9132,{"lat":59,"lon":58},[62,66],{"name":63,"role":27,"phone":64,"phoneExt":10,"email":65},"Katelyn J Rittenhouse, MD","919-966-5281","katelyn_rittenhouse@med.unc.edu",{"name":67,"role":27,"phone":64,"phoneExt":10,"email":68},"Jeffrey S.A. Stringer, MD","jeffrey_stringer@med.unc.edu",{"facility":70,"status":33,"city":71,"state":72,"zip":10,"country":73,"countryCode":74,"cosmosGeoPoint":75,"geoPoint":79,"contacts":80},"University of Saskatchewan","Saskatoon","Saskatchewan","Canada","CA",{"type":40,"coordinates":76},[77,78],-106.66892,52.13238,{"lat":78,"lon":77},[81],{"name":82,"role":27,"phone":83,"phoneExt":10,"email":84},"Scott Adams, MD, PhD","(306) 655-2402","scott.adams@usask.ca",{"facility":86,"status":33,"city":87,"state":10,"zip":10,"country":88,"countryCode":89,"cosmosGeoPoint":90,"geoPoint":94,"contacts":95},"University of Rwanda","Kigali","Rwanda","RW",{"type":40,"coordinates":91},[92,93],30.05885,-1.94995,{"lat":93,"lon":92},[96],{"name":97,"role":27,"phone":98,"phoneExt":10,"email":99},"Stephen Rulisa, MD, PhD","+250788571436","s.rulisa@gmail.com",{"facility":101,"status":33,"city":102,"state":10,"zip":10,"country":103,"countryCode":104,"cosmosGeoPoint":105,"geoPoint":109,"contacts":110},"University Teaching Hospital","Lusaka","Zambia","ZM",{"type":40,"coordinates":106},[107,108],28.28713,-15.40669,{"lat":108,"lon":107},[111],{"name":112,"role":27,"phone":113,"phoneExt":10,"email":114},"Margaret Kasaro, MBChB, MMed, MSc","+260963223210","margaret.kasaro@unclusaka.org",{"type":116,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[118],{"name":119,"class":6},"Bill and Melinda Gates Foundation","100641551","prospective-evaluation-of-an-ai-diagnostic-ultrasound-tool-for-fetal-weight-estimation-100641551",false,"NCT07661433","Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation","Z 32503 - Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation","Inclusion Criteria:\n\n* 18 years of age or older\n* Viable intrauterine pregnancy\n* Delivery expected within one week of study procedures between 24 0\u002F7 and 42 6\u002F7 weeks, including participants with a scheduled induction or cesarean delivery on a known date, or those admitted in spontaneous labor\n* Ability and willingness to provide written informed consent\n* Willingness to comply with all study procedures\n\nExclusion Criteria:\n\n* Maternal body mass index ≥ 40 kg\u002Fm\\^2\n* Multiple gestation (i.e., twins or higher order)\n* Known major fetal malformation or anomaly\n* Any maternal condition (medical, psychological, or social) that, in the opinion of the study team, may interfere with study participation or data integrity.","FEMALE","18 Years",{"count":130,"type":131},1000,"ESTIMATED","OBSERVATIONAL","Purpose: The primary objective of this study is to assess the diagnostic accuracy of an AI-enabled ultrasound tool for estimating fetal weight Participants: 1,000 pregnant individuals Procedures (methods): This prospective diagnostic accuracy study will enroll 1,000 pregnant individuals within one week of anticipated delivery. At a single visit, each participant will undergo two ultrasound assessments: (1) standardized sweeps for AI analysis (performed by both specialist and nonspecialist users), (2) specialist-performed fetal biometry.",[135,136,137,138],"Fetal Weight","Pregnancy","Machine Learning","Pregnancy - Prenatal Testing","2026-07-06",{"date":141,"type":142},"2026-07-08","ACTUAL",{"date":144,"type":142},"2026-06-29",{"date":146,"type":131},"2026-12",{"name":5,"class":6},5]