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Journal Article Review Epublish 100 citations

PubMed: 36552986 DOI: 10.3390/diagnostics12122979

The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks.

Diagnostics (Basel) 12(12)

Authors: Sanja Medenica, Dusan Zivanovic, Ljubica Batkoska, Susanna Marinelli, Giuseppe Basile, Antonio Perino, Gaspare Cucinella, Giuseppe Gullo, Simona Zaami

Affiliations

  • Department of Endocrinology, Internal Medicine Clinic, Clinical Center of Montenegro, School of Medicine, University of Montenegro, 81000 Podgorica, Montenegro.
  • Clinic of Endocrinology, Diabetes and Metabolic Disorders, University Clinical Center of Serbia, 11000 Belgrade, Serbia.
  • Medical Faculty, Ss. Cyril and Methodius University of Skopje, 1000 Skopje, North Macedonia.
  • School of Law, Polytecnic University of Marche, 60121 Ancona, Italy.
  • IRCCS Orthopedic Institute Galeazzi, 20161 Milan, Italy.
  • Department of Obstetrics and Gynecology, Villa Sofia Cervello Hospital, IVF UNIT, University of Palermo, 90146 Palermo, Italy.
  • Department of Anatomical, Histological, Forensic and Orthopedic Sciences, "Sapienza" University of Rome, 00161 Rome, Italy.

Abstract

Infertility is a global health issue affecting women and men of reproductive age with increasing incidence worldwide, in part due to greater awareness and better diagnosis. Assisted reproduction technologies (ART) are considered the ultimate step in the treatment of infertility. Recently, artificial intelligence (AI) has been progressively used in the many fields of medicine, integrating knowledge and computer science through machine learning algorithms. AI has the potential to improve infertility diagnosis and ART outcomes estimated as pregnancy and/or live birth rate, especially with recurrent ART failure. A broad-ranging review has been conducted, focusing on clinical AI applications up until September 2022, which could be estimated in terms of possible applications, such as ultrasound monitoring of folliculogenesis, endometrial receptivity, embryo selection based on quality and viability, and prediction of post implantation embryo development, in order to eliminate potential contributing risk factors. Oocyte morphology assessment is highly relevant in terms of successful fertilization rate, as well as during oocyte freezing for fertility preservation, and substantially valuable in oocyte donation cycles. AI has great implications in the assessment of male infertility, with computerised semen analysis systems already in use and a broad spectrum of possible AI-based applications in environmental and lifestyle evaluation to predict semen quality. In addition, considerable progress has been made in terms of harnessing AI in cases of idiopathic infertility, to improve the stratification of infertile/fertile couples based on their biological and clinical signatures. With AI as a very powerful tool of the future, our review is meant to summarise current AI applications and investigations in contemporary reproduction medicine, mainly focusing on the nonsurgical aspects of it; in addition, the authors have briefly explored the frames of reference and guiding principles for the definition and implementation of legal, regulatory, and ethical standards for AI in healthcare.

MeSH

Intelligence, Reproduction, Fertility, Computers, Infertility, Oocytes, Diagnosis, Therapeutics, Artificial Intelligence

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