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AI-Driven Oocyte Scoring Enhances IVF Success Rates – RBMO
RBMO/LinkedIn
Feb 7, 2026, 14:09

AI-Driven Oocyte Scoring Enhances IVF Success Rates – RBMO

Reproductive BioMedicine Online shared a post on LinkedIn:

“The findings of this study show a significant association between key morphokinetic and morphological features from fertilisation through blastulation using the deep learning–based oocyte assessment system, MAGENTA.

The authors say:

‘The MAGENTA score may reflect the integrity of the cell membrane and cytoplasm and the organisation of the cytoskeleton during fertilisation and the early cleavage stages. These factors contribute to later development, including cell polarisation during compaction, followed by blastulation and expansion. Further, the sum of the MAGENTA scores can be used to estimate the cumulative live birth rate per retrieval. These results support the clinical utility of AI-based oocyte scoring in IVF and provide further biological insight into predictors of early embryo development driven by oocyte quality.’

The full paper is available now as a pre-proof to RBMO subscribers from our in-press articles section now.”

Title: Artificial intelligence-driven oocyte scores link early morphokinetics to embryo outcomes following intracytoplasmic sperm injection

Authors: Nanoha Fujiwara, Kenji Ezoe, Tetsuya Miki, Tsubasa Takahashi, Lais Vanzella, Natalie Mercuri, Jullin Fjeldstad, Parisa Mojiri, Dan Nayot, Tomoko Kuroda, Keiichi Kato

Oocyte

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blastulation cell polarisation Dan Nayot early cleavage stages embryo development Fertility Fertility News Jullin Fjeldstad Keiichi Kato Kenji Ezoe Laís Vanzella live birth rate MAGENTA Nanoha Fujiwara Natalie Mercuri oocyte Parisa Mojiri RBMO Reproductive BioMedicine Online reproductive health Reproductive Medicine Tetsuya Miki Tomoko Kuroda Tsubasa Takahashi
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