A machine learning model for predicting fertilization following short‐term insemination using embryo images
Abstract Purpose This study established a machine learning model (MLM) trained on embryo images to predict fertilization following short‐term insemination for early rescue ICSI and compared its predictive performance with the embryologist's manual classification. Methods Embryo images at 4.5 an...
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| Main Authors: | Masato Saito, Hirofumi Haraguchi, Ikumi Nakajima, Shinya Fukuda, Chenghua Zhu, Norio Masuya, Kazunori Matsumoto, Yuya Yoshikawa, Tomoki Tanaka, Satoshi Kishigami, Leona Matsumoto |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Reproductive Medicine and Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/rmb2.12649 |
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