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

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

Recruiting
18 years and older
Female
Phase N/A

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Overview

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

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.

Study details
    Fetal Weight
    Pregnancy
    Machine Learning
    Pregnancy - Prenatal Testing

NCT07661433

University of North Carolina, Chapel Hill

11 July 2026

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