Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.

Journal: Fertility and sterility
Published Date: Feb 17, 2024

Abstract

OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).

Authors

  • Chen Wang
    Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Anna L V Johansson
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Cina Nyberg
    Livio Fertilitetscentrum Kungsholmen, Stockholm, Sweden; Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.
  • Anuj Pareek
    Stanford University, Center for Artificial Intelligence in Medicine & Imaging, Stanford, CA, 94304, US.
  • Catarina Almqvist
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Sonia Hernandez-Diaz
    Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Anna S Oberg
    Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

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