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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الحاوية / القاعدة:	Scientific Reports
المؤلفون الرئيسيون:	Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	Nature Portfolio 2025-07-01
الموضوعات:	Machine learning algorithm Biomechanical Microfluidic Oocyte In vitro fertilization (IVF)
الوصول للمادة أونلاين:	https://doi.org/10.1038/s41598-025-11810-4