A machine learning model for predicting fertilization following short‐term insemination using embryo images

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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Bibliographic Details
Main Authors: Masato Saito, Hirofumi Haraguchi, Ikumi Nakajima, Shinya Fukuda, Chenghua Zhu, Norio Masuya, Kazunori Matsumoto, Yuya Yoshikawa, Tomoki Tanaka, Satoshi Kishigami, Leona Matsumoto
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Reproductive Medicine and Biology
Subjects:
cytoplasm
early rescue ICSI
fertilization
machine learning
short‐term insemination
Online Access:https://doi.org/10.1002/rmb2.12649
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