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NCT07661433Recruiting

Prospective Evaluation of an AI Diagnostic Ultrasound Tool for Fetal Weight Estimation

University of North Carolina, Chapel Hill

Start Date

6/29/2026

Completion Date

12/1/2026

Summary

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.

Eligibility Criteria

Age Range: 18 years to No maximum

Inclusion Criteria: * 18 years of age or older * Viable intrauterine pregnancy * Delivery expected within one week of study procedures between 24 0/7 and 42 6/7 weeks, including participants with a scheduled induction or cesarean delivery on a known date, or those admitted in spontaneous labor * Ability and willingness to provide written informed consent * Willingness to comply with all study procedures Exclusion Criteria: * Maternal body mass index ≥ 40 kg/m\^2 * Multiple gestation (i.e., twins or higher order) * Known major fetal malformation or anomaly * Any maternal condition (medical, psychological, or social) that, in the opinion of the study team, may interfere with study participation or data integrity.

Interventions

DIAGNOSTIC_TEST

AI ultrasound diagnostic tool for fetal weight estimation

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Conditions

Fetal WeightPregnancyMachine LearningPregnancy - Prenatal Testing

Locations

Ochsner Health

New Orleans, Louisiana 70115

United States

University of North Carolina

Chapel Hill, North Carolina 27516

United States

University of Saskatchewan

Saskatoon, Saskatchewan

Canada

University of Rwanda

Kigali,

Rwanda

University Teaching Hospital

Lusaka,

Zambia