Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study.

Journal: Journal of medical Internet research
PMID: 38830209

Abstract

BACKGROUND: Current embryo assessment methods for in vitro fertilization depend on subjective morphological assessments. Recently, artificial intelligence (AI) has emerged as a promising tool for embryo assessment; however, its clinical efficacy and trustworthiness remain unproven. Simulation studies may provide additional evidence, provided that they are meticulously designed to mitigate bias and variance.

Authors

  • Hyung Min Kim
  • Hyoeun Kang
    School of Computer Science and Engineering, Pusan National University, Busan 609735, Korea.
  • Chaeyoon Lee
    AI Lab, Kai Health, Seoul, Republic of Korea.
  • Jong Hyuk Park
    IVF Clinic, Miraewaheemang Hospital, Seoul, Republic of Korea.
  • Mi Kyung Chung
    IVF Clinic, Seoul Rachel Fertility Center, Seoul, Republic of Korea.
  • Miran Kim
    University of Texas, Health Science Center.
  • Na Young Kim
    Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul, Korea.
  • Hye Jun Lee
    Kai Health, Seoul, Republic of Korea.

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