Machine learning and microfluidic integration for oocyte quality prediction

Machine learning and microfluidic integration for oocyte quality prediction

Abstract Despite advancements in in vitro fertilization (IVF) over the past 30 years, its outcome effectiveness remains low (20–40%). This study introduces a microfluidic-based machine learning framework to improve predictive accuracy in oocyte quality assessment. Immature oocytes were recorded as t...

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Bibliographic Details
Main Authors: Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Machine learning algorithm
Biomechanical
Microfluidic
Oocyte
In vitro fertilization (IVF)
Online Access:https://doi.org/10.1038/s41598-025-11810-4
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