Empathetic application of machine learning may address appropriate utilization of ART.

Journal: Reproductive biomedicine online
Published Date:

Abstract

The value of artificial intelligence to benefit infertile patients is a subject of debate. This paper presents the experience of one aspect of artificial intelligence, machine learning, coupled with patient empathy to improve utilization of assisted reproductive technology (ART), which is an important aspect of care that is under-recognized. Although ART provides very effective options for infertile patients to build families, patients often discontinue ART when further treatment is likely to be beneficial and most of these patients do not achieve pregnancy without medical aid. Use of ART is only in part dependent on financial considerations; stress and other factors play a major role, as shown by high discontinuation rates despite reimbursement. This commentary discusses challenges and strategies to providing personalized ART prognostics based on machine learning, and presents a case study where appropriate use of such prognostics in ART centres is associated with a trend towards increased ART utilization.

Authors

  • Julian Jenkins
    Repromed Sàrl, Crassier 1263, Switzerland; Medical Affairs, Gedeon Richter Plc / PregLem SA, 41A Route de Frontenex, Geneva 1207, Switzerland. Electronic address: julian.jenkins@repromed.net.
  • Sheryl van der Poel
    Population Council, One Dag Hammarskjold Plaza, New York, NY 10017, USA.
  • Jan Krüssel
    Department of Obstetrics and Gynecology, Heinrich-Heine University Medical Centre, Düsseldorf, Germany.
  • Ernesto Bosch
    Instituto Valenciano de Infertilidad (IVI-RMA), Valencia, Spain.
  • Scott M Nelson
    School of Medicine, University of Glasgow, Glasgow G31 2ER, UK.
  • Anja Pinborg
    Fertility Clinic, Section 4071, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100, Copenhagen, Denmark.
  • Mylene M W Yao
    Univfy Inc., 1 1st Street, Los Altos, CA, USA.