Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps.

Journal: JAMA
PMID: 39088200

Abstract

IMPORTANCE: Accurate assessment of gestational age (GA) is essential to good pregnancy care but often requires ultrasonography, which may not be available in low-resource settings. This study developed a deep learning artificial intelligence (AI) model to estimate GA from blind ultrasonography sweeps and incorporated it into the software of a low-cost, battery-powered device.

Authors

  • Jeffrey S A Stringer
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Teeranan Pokaprakarn
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Juan C Prieto
    Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Bellington Vwalika
    Department of Obstetrics and Gynaecology, University of Zambia School of Medicine, Lusaka, Zambia.
  • Srihari V Chari
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Ntazana Sindano
    UNC Global Projects - Zambia LLC, Lusaka, Zambia.
  • Bethany L Freeman
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Bridget Sikapande
    UNC Global Project-Zambia, Lusaka, Zambia.
  • Nicole M Davis
    Innovation Office, Mass General Brigham, Somerville, Massachusetts.
  • Yuri V Sebastião
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Nelly M Mandona
    UNC Global Project-Zambia, Lusaka, Zambia.
  • Elizabeth M Stringer
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Chiraz Benabdelkader
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
  • Mutinta Mungole
    UNC Global Project-Zambia, Lusaka, Zambia.
  • Filson M Kapilya
    UNC Global Project-Zambia, Lusaka, Zambia.
  • Nariman Almnini
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Arieska N Diaz
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Brittany A Fecteau
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill.
  • Michael R Kosorok
    Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC.
  • Stephen R Cole
    Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill.
  • Margaret P Kasaro
    Department of Obstetrics and Gynecology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.

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