Peer-Reviewed Publication
Ultrasound Obstet Gynecol2023;62(3):353-360.September 1, 2023Journal Article
Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination.
J J Stirnemann1,2, R Besson3, E Spaggiari1,2,4, S Rojo3, F Loge3, H Peyro-Saint-Paul3, S Allassonniere5,6, E Le Pennec6,7, C Hutchinson8, N Sebire8, Y Ville1,2
1Department of Obstetrics and Maternal-Fetal Medicine, Necker-Enfants Malades Hospital, AP-HP, Paris, France.
2EA7328 Université de Paris, IMAGINE Institute, Paris, France.
3SONIO SAS, Paris, France.
4Department of Histology-Embryology and Cytogenetics, Unit of Embryo and Fetal Pathology, Necker-Enfants Malades Hospital, AP-HP, Paris, France.
5School of Medicine, Université de Paris, INRIA EPI HEKA, INSERM UMR 1138, Sorbonne Université, Paris, France.
6Center for Applied Mathematics, Ecole Polytechnique, Institut Polytechnique de Paris, Paris, France.
7Xpop, INRIA Saclay Center, Paris, France.
8NIHR Great Ormond Street Hospital Biomedical Research Centre, London, UK.
Abstract
OBJECTIVE: Prenatal diagnosis of a rare disease on ultrasound relies on a physician's ability to remember an intractable amount of knowledge. We developed a real-time decision support system (DSS) that suggests, at each step of the examination, the next phenotypic feature to assess, optimizing the diagnostic pathway to the smallest number of possible diagnoses. The objective of this study was to e…
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