Enhancing clinical utility: deep learning-based embryo scoring model for non-invasive aneuploidy prediction.

Journal: Reproductive biology and endocrinology : RB&E
PMID: 38778410

Abstract

BACKGROUND: The best method for selecting embryos ploidy is preimplantation genetic testing for aneuploidies (PGT-A). However, it takes more labour, money, and experience. As such, more approachable, non- invasive techniques were still needed. Analyses driven by artificial intelligence have been presented recently to automate and objectify picture assessments.

Authors

  • Bing-Xin Ma
    Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
  • Guang-Nian Zhao
    Department of Gynecological Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
  • Zhi-Fei Yi
    Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
  • Yong-Le Yang
    Reproductive Medicine Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
  • Lei Jin
    Department of Chemistry, University of Connecticut, Storrs, Connecticut 06269, United States.
  • Bo Huang
    Geriatrics Division, Department of Medicine, Peking University First Hospital, Beijing 100034, China.

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