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

In a heterogeneous, multicenter dataset, the software reliably identified predefined ultrasound findings suggestive of congenital malformations. These results support its potential as a real-time assistant to standardize interpretation and to flag suspicious findings.

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Publication Details

Journal
Obstetrics and Gynecology
Published
2026-01-08
DOI
https://doi.org/10.1097/aog.0000000000006164
Primary Topic
Fetal and Pediatric Neurological Disorders
Type
article
Field-Weighted Citation Impact
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article

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

R. S. Besson, Şifa Turan, Nicolas Fries, Frédéric Logé-Munerel et al.
Obstetrics and Gynecology
Fetal and Pediatric Neurological Disorders
article

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

R. S. Besson, Şifa Turan, Nicolas Fries, Frédéric Logé-Munerel, Julien Stirnemann, Clémentine Morisset, Yves Ville, Yinka Oyelese, Vianney Debavelaere
article en

Abstract

In a heterogeneous, multicenter dataset, the software reliably identified predefined ultrasound findings suggestive of congenital malformations. These results support its potential as a real-time assistant to standardize interpretation and to flag suspicious findings.

Obstetrics and Gynecology
University of Maryland, Baltimore (US), Beth Israel Deaconess Medical Center (US), Université Paris Cité (FR)
Openalex Percentile: Top 93%
Fetal and Pediatric Neurological Disorders
DOISourceOpenAlex
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