[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100641551":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":20,"centralContacts":24,"locations":30,"responsibleParty":113,"collaborators":115,"id":118,"slug":119,"hasResults":120,"nctId":121,"briefTitle":122,"officialTitle":123,"acronym":10,"eligibilityCriteria":124,"healthyVolunteers":120,"sex":125,"minAge":126,"maxAge":10,"enrollmentInfo":127,"targetDuration":10,"studyType":130,"phases":10,"briefSummary":131,"conditions":132,"keywords":10,"overallStatus":137,"whyStopped":10,"lastUpdateSubmitDate":138,"lastUpdatePostDateStruct":139,"startDateStruct":142,"completionDateStruct":144,"leadSponsor":146,"locationsCount":147},{"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",[31,49,67,83,98],{"facility":32,"status":10,"city":33,"state":34,"zip":35,"country":36,"countryCode":37,"cosmosGeoPoint":38,"geoPoint":43,"contacts":44},"Ochsner Health","New Orleans","Louisiana","70115","United States","US",{"type":39,"coordinates":40},"Point",[41,42],-90.07507,29.95465,{"lat":42,"lon":41},[45],{"name":46,"role":27,"phone":47,"phoneExt":10,"email":48},"Will Williams, MD","504-842-5574","frank.williams2@ochsner.org",{"facility":50,"status":10,"city":51,"state":52,"zip":53,"country":36,"countryCode":37,"cosmosGeoPoint":54,"geoPoint":58,"contacts":59},"University of North Carolina","Chapel Hill","North Carolina","27516",{"type":39,"coordinates":55},[56,57],-79.05584,35.9132,{"lat":57,"lon":56},[60,64],{"name":61,"role":27,"phone":62,"phoneExt":10,"email":63},"Katelyn J Rittenhouse, MD","919-966-5281","katelyn_rittenhouse@med.unc.edu",{"name":65,"role":27,"phone":62,"phoneExt":10,"email":66},"Jeffrey S.A. Stringer, MD","jeffrey_stringer@med.unc.edu",{"facility":68,"status":10,"city":69,"state":70,"zip":10,"country":71,"countryCode":72,"cosmosGeoPoint":73,"geoPoint":77,"contacts":78},"University of Saskatchewan","Saskatoon","Saskatchewan","Canada","CA",{"type":39,"coordinates":74},[75,76],-106.66892,52.13238,{"lat":76,"lon":75},[79],{"name":80,"role":27,"phone":81,"phoneExt":10,"email":82},"Scott Adams, MD, PhD","(306) 655-2402","scott.adams@usask.ca",{"facility":84,"status":10,"city":85,"state":10,"zip":10,"country":86,"countryCode":87,"cosmosGeoPoint":88,"geoPoint":92,"contacts":93},"University of Rwanda","Kigali","Rwanda","RW",{"type":39,"coordinates":89},[90,91],30.05885,-1.94995,{"lat":91,"lon":90},[94],{"name":95,"role":27,"phone":96,"phoneExt":10,"email":97},"Stephen Rulisa, MD, PhD","+250788571436","s.rulisa@gmail.com",{"facility":99,"status":10,"city":100,"state":10,"zip":10,"country":101,"countryCode":102,"cosmosGeoPoint":103,"geoPoint":107,"contacts":108},"University Teaching Hospital","Lusaka","Zambia","ZM",{"type":39,"coordinates":104},[105,106],28.28713,-15.40669,{"lat":106,"lon":105},[109],{"name":110,"role":27,"phone":111,"phoneExt":10,"email":112},"Margaret Kasaro, MBChB, MMed, MSc","+260963223210","margaret.kasaro@unclusaka.org",{"type":114,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[116],{"name":117,"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":128,"type":129},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.",[133,134,135,136],"Fetal Weight","Pregnancy","Machine Learning","Pregnancy - Prenatal Testing","NOT_YET_RECRUITING","2026-06-22",{"date":140,"type":141},"2026-06-25","ACTUAL",{"date":143,"type":129},"2026-06",{"date":145,"type":129},"2026-12",{"name":5,"class":6},5]