Machine learning center-specific models show improved IVF live birth predictions over US national registry-based model

Machine learning center-specific models show improved IVF live birth predictions over US national registry-based model

Abstract Expanding in vitro fertilization (IVF) access requires improved patient counseling and affordability via cost-success transparency. Clinicians ask how two types of live birth prediction (LBP) models perform: machine learning, center-specific (MLCS) models and the multicenter, US national re...

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Main Authors: Mylene W. M. Yao, Elizabeth T. Nguyen, Matthew G. Retzloff, L. April Gago, John E. Nichols, John F. Payne, Barry A. Ripps, Michael Opsahl, Jeremy Groll, Ronald Beesley, Gregory Neal, Jaye Adams, Lorie Nowak, Trevor Swanson, Xiaocong Chen
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-58744-z
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https://doi.org/10.1038/s41467-025-58744-z

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