Artificial intelligence for sperm selection-a systematic review.

Journal: Fertility and sterility
Published Date:

Abstract

Despite the increasing number of assisted reproductive technologies based treatments being performed worldwide, there has been little improvement in fertilization and pregnancy outcomes. Male infertility is a major contributing factor, and sperm evaluation is a crucial step in diagnosis and treatment. However, embryologists face the daunting task of selecting a single sperm from millions in a sample based on various parameters, which can be time-consuming, subjective, and may even cause damage to the sperm, deeming them unusable for fertility treatments. Artificial intelligence algorithms have revolutionized the field of medicine, particularly in image processing, because of their discerning abilities, efficacy, and reproducibility. Artificial intelligence algorithms have the potential to address the challenges of sperm selection with their large-data processing capabilities and high objectivity. These algorithms could provide valuable assistance to embryologists in sperm analysis and selection. Furthermore, these algorithms could continue to improve over time as larger and more robust datasets become available for their training.

Authors

  • Panagiotis Cherouveim
    Division of Reproductive Endocrinology and Infertility, Vincent Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Suite 10A, Boston, MA, 02114, USA.
  • Constantine Velmahos
    University of Massachusetts Chan Medical School, Worcester, Massachusetts.
  • Charles L Bormann
    Department of Obstetrics and Gynecology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.