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Machine learning–based prediction of IVF/ICSI outcomes in male factor infertility highlighting couple-level BMI

BackgroundMost clinical prediction models for assisted reproductive technology focus primarily on female ovarian reserve markers and often under-represent male factors and the metabolic status of both partners. Additionally, traditional parametric models may have limited ability to capture nonlinear...

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Bibliografiset tiedot
Päätekijät: Hu Li, Jie Gao, Yiran Li
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Frontiers Media S.A. 2026-02-01
Sarja:Frontiers in Endocrinology
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Linkit:https://www.frontiersin.org/articles/10.3389/fendo.2026.1772106/full
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