Empathetic application of machine learning may address appropriate utilization of ART

Research output: Contribution to journalComment/debateResearchpeer-review

  • Julian Jenkins
  • Sheryl van der Poel
  • Jan Krüssel
  • Ernesto Bosch
  • Scott M. Nelson
  • Pinborg, Anja
  • Mylene M.W. Yao

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.

Original languageEnglish
JournalReproductive BioMedicine Online
Volume41
Issue number4
Pages (from-to)573-577
Number of pages5
ISSN1472-6483
DOIs
Publication statusPublished - 2020

    Research areas

  • ART utilization, Artificial intelligence, IVF drop-outs, Machine learning, Patient empathy, Prognostication

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