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A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images.

Zaowen LiaoChaoyu YanJianbo WangNingfeng ZhangHuan YangChenghao LinHaiyue ZhangWenjun WangWeizhong Li
Published in: Artif. Intell. Medicine (2024)
Keyphrases
  • deep learning
  • microscope images
  • ground truth
  • machine learning
  • unsupervised learning
  • high dimensional
  • weakly supervised
  • cross sections