Multicenter Evaluation of an Artificial Intelligence System for Automatic Recognition of Fetal Ultrasound Findings Suggestive of Congenital Malformations.

Clémentine Morisset¹, Frédéric Logé-Munerel, Vianney Debavelaere, Rémi Besson, Sifa Turan, Nicolas Fries, Julien Stirnemann, Yinka Oyelese, Yves Ville

¹Sonio SAS, and Obstetrics, Paris Descartes University, Necker-Enfants Malades Hospital, Paris, and the IMAGYN'ECHO Medical Center, Montpellier, France; the Department of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland, Baltimore, Maryland; and the Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts.

PubMed DOI

Abstract

OBJECTIVE: To evaluate the diagnostic performance of an artificial intelligence (AI) system for detecting eight abnormal fetal ultrasound findings across cephalic, thoracic, and abdominal regions in routine, unfiltered, multicenter images. METHODS: We performed a multicenter, retrospective evaluation of an AI software that detects eight abnormal ultrasound findings on still images. Ground truth w…

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