Explainable artificial intelligence to identify follicles that optimize clinical outcomes during assisted conception

Explainable artificial intelligence to identify follicles that optimize clinical outcomes during assisted conception

Abstract Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple ‘rules-of-thumb’. Machine learning technique...

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Bibliographic Details
Main Authors: Simon Hanassab, Scott M. Nelson, Artur Akbarov, Arthur C. Yeung, Artsiom Hramyka, Toulin Alhamwi, Rehan Salim, Alexander N. Comninos, Geoffrey H. Trew, Tom W. Kelsey, Thomas Heinis, Waljit S. Dhillo, Ali Abbara
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-55301-y

Internet

https://doi.org/10.1038/s41467-024-55301-y

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