Should there be an "AI" in TEAM? Embryologists selection of high implantation potential embryos improves with the aid of an artificial intelligence algorithm.

Journal: Journal of assisted reproduction and genetics
Published Date: Oct 1, 2021

Abstract

PURPOSE: A deep learning artificial intelligence (AI) algorithm has been demonstrated to outperform embryologists in identifying euploid embryos destined to implant with an accuracy of 75.3% (1). Our aim was to evaluate the performance of highly trained embryologists in selecting top quality day 5 euploid blastocysts with and without the aid of a deep learning algorithm.

Authors

  • V W Fitz
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • M K Kanakasabapathy
    Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • P Thirumalaraju
    Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • H Kandula
    Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • L B Ramirez
    Northwell Health Fertility, Manhasset, NY, USA.
  • L Boehnlein
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, University of Wisconsin, Madison, WI, USA.
  • J E Swain
    CCRM Fertility Network, Lone Tree, CO, USA.
  • C L Curchoe
    CCRM Fertility Orange County, Newport Beach, CA, USA.
  • K James
    The Deborah Kelly Center for Outcomes Research, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
  • I Dimitriadis
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • I Souter
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • C L Bormann
    Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. cbormann@partners.org.
  • H Shafiee
    Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. hshafiee@bwh.harvard.edu.

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