Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation

Abstract Background Artificial intelligence (AI) models analyzing embryo time-lapse images have been developed to predict the likelihood of pregnancy following in vitro fertilization (IVF). However, limited research exists on methods ensuring AI consistency and reliability in clinical settings durin...

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Bibliographic Details
Main Authors:	D. Gilboa, Akhil Garg, M. Shapiro, M. Meseguer, Y. Amar, N. Lustgarten, N. Desai, T. Shavit, V. Silva, A. Papatheodorou, A. Chatziparasidou, S. Angras, J. H. Lee, L. Thiel, C. L. Curchoe, Y. Tauber, D. S. Seidman
Format:	Article
Language:	English
Published:	BMC 2025-01-01
Series:	Reproductive Biology and Endocrinology
Subjects:	Artificial intelligence Time lapse imaging Embryo ranking Machine learning
Online Access:	https://doi.org/10.1186/s12958-025-01351-w
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Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation

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