Predictive modeling of pregnancy outcomes utilizing multiple machine learning techniques for in vitro fertilization-embryo transfer.

Journal: BMC pregnancy and childbirth
PMID: 40108498

Abstract

OBJECTIVE: This study aims to investigate the influencing factors of pregnancy outcomes during in vitro fertilization and embryo transfer (IVF-ET) procedures in clinical practice. Several prediction models were constructed to predict pregnancy outcomes and models with higher accuracy were identified for potential implementation in clinical settings.

Authors

  • Ru Bai
    Reproductive Centre, The Affiliated Hospital of Inner Mongolia Medical University, No.1 of North Tongdao Road, Huimin District, Hohhot, 010000, Inner Mongolia Autonomous Region, China.
  • Jia-Wei Li
    Department of Medical Ultrasound, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, People's Republic of China.
  • Xia Hong
    Reproductive Centre, The Affiliated Hospital of Inner Mongolia Medical University, No.1 of North Tongdao Road, Huimin District, Hohhot, 010000, Inner Mongolia Autonomous Region, China.
  • Xiao-Yue Xuan
    Reproductive Centre, The Affiliated Hospital of Inner Mongolia Medical University, No.1 of North Tongdao Road, Huimin District, Hohhot, 010000, Inner Mongolia Autonomous Region, China.
  • Xiao-He Li
    State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University, Tianjin 300071, China.
  • Ya Tuo
    Department of Biochemistry and Physiology, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China.

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