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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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 |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-024-55301-y |
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