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AI in the treatment of fertility: key considerations

Journal of Assisted Reproduction and Genetics volume 37, pages 2817–2824 (2020)Cite this article

Abstract

Artificial intelligence (AI) has been proposed as a potential tool to help address many of the existing problems related with empirical or subjective assessments of clinical and embryological decision points during the treatment of infertility. AI technologies are reviewed and potential areas of implementation of algorithms are discussed, highlighting the importance of following a proper path for the development and validation of algorithms, including regulatory requirements, and the need for ecosystems containing enough quality data to generate it. As evidenced by the consensus of a group of experts in fertility if properly developed, it is believed that AI algorithms may help practitioners from around the globe to standardize, automate, and improve IVF outcomes for the benefit of patients. Collaboration is required between AI developers and healthcare professionals to make this happen.

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Acknowledgments

Fertility AI Forum Group: Gerard Letterie, Integramed; Pascual Sánchez, Ginemed; Geoff Trew, The Fertility Partnership; Jason Swain, CCRM Management Co.; Marcos Meseguer, IVIRMA; Dan Nayot, Trio Fertility; Alison Campbell, CARE; Ian Huang, Storck–Binflux; Jan Choma, Cognexa; Kevin Loewke, DANA; María Paola Piqueras, Ginemed; Paul Nader, Baby Sentry; Michael Schindler, Meditex; Marck Marcom, Ideas EMR; Ed Vom, Planet Innovation; Eleanora Lippolis, Merck; Sebastian Bohl, Merck, Jan Kirsten, Merck; Daniel Abshagen, Merck; Diego Ezcurra, Merck.

Author information

Authors and Affiliations

  1. CCRM Fertility Network, Lone Tree, CO, USA

    Jason Swain

  2. Ovation Fertility and Texas Fertility Centers, Austin and San Antonio, TX, USA

    Matthew Tex VerMilyea

  3. Instituto Valenciano de Infertilidad (IVI) Valencia, INCLIVA-Universidad de Valencia, Valencia, Spain

    Marcos Meseguer

  4. EMD Serono, One Technology Place, Rockland, MA02370, USA

    Diego Ezcurra

Authors
  1. Jason Swain
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  2. Matthew Tex VerMilyea
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  3. Marcos Meseguer
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  4. Diego Ezcurra
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Consortia

Fertility AI Forum Group

  • Diego Ezcurra
  • , Gerard Letterie
  • , Pascual Sánchez
  • , Geoff Trew
  • , Jason Swain
  • , Marcos Meseguer
  • , Dan Nayot
  • , Alison Campbell
  • , Ian Huangv
  • , Jan Choma
  • , Kevin Loewke
  • , María Paola Piqueras
  • , Paul Nader
  • , Michael Schindler
  • , Eleanora Lippolis
  • , Sebastian Bohl
  • , Jan Kirsten
  •  & Daniel Abshagen

Corresponding author

Correspondence to Diego Ezcurra.

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Swain, J., VerMilyea, M.T., Meseguer, M. et al. AI in the treatment of fertility: key considerations. J Assist Reprod Genet 37, 2817–2824 (2020). https://doi.org/10.1007/s10815-020-01950-z

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  • DOI: https://doi.org/10.1007/s10815-020-01950-z

Keywords

  • fertility
  • AI
  • algorithms
  • embryos