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AI in the treatment of fertility: key considerations

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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.

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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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