Machine learning vs. classic statistics for the prediction of IVF outcomes.

Abstract

Authors

• Zohar Barnett-Itzhaki
  Public Health Services, Ministry of Health, 39 Yirmiyahu Street, 9446724, Jerusalem, Israel. zoharba@ruppin.ac.il.
• Miriam Elbaz
  Jerusalem College of Technology, Jerusalem, Israel.
• Rachely Butterman
  Bioinformatics Department, School of Life and Health Sciences, Jerusalem College of Technology, Jerusalem, Israel.
• Devora Amar
  Bioinformatics Department, School of Life and Health Sciences, Jerusalem College of Technology, Jerusalem, Israel.
• Moshe Amitay
  Bioinformatics Department, School of Life and Health Sciences, Jerusalem College of Technology, Jerusalem, Israel.
• Catherine Racowsky
  Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
• Raoul Orvieto
  Department of Obstetrics and Gynecology, Sheba Medical Center, 52561, Ramat Gan, Israel.
• Russ Hauser
  Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
• Andrea A Baccarelli
  Laboratory of Precision Environmental Biosciences, Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, 10032, USA.
• Ronit Machtinger
  Department of Obstetrics and Gynecology, Sheba Medical Center, 52561, Ramat Gan, Israel.

Keywords

External Resources