Empathetic application of machine learning may address appropriate utilization of ART. Issue 4 (October 2020)

• Record Type: Journal Article
• Authors: Jenkins, Julian; van der Poel, Sheryl; Krüssel, Jan; Bosch, Ernesto; Nelson, Scott M.; Pinborg, Anja; Yao, Mylene M.W.
• Is Part Of: Reproductive biomedicine online. Volume 41:Issue 4(2020)
• Page Start: 573
• Page End: 577
• Publication Date: 2020-10
• Subjects: ART utilization -- Artificial intelligence -- IVF drop-outs -- Machine learning -- Patient empathy -- Prognostication; Human reproductive technology -- Periodicals; Human embryo -- Periodicals; Reproduction -- Periodicals; 616.692
• DOI: 10.1016/j.rbmo.2020.07.005
• Languages: English
• ISSNs: 1472-6483

Abstract

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.