4.7 Review

Artificial intelligence in the fertility clinic: status, pitfalls and possibilities

Journal

HUMAN REPRODUCTION
Volume 36, Issue 9, Pages 2429-2442

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/humrep/deab168

Keywords

artificial intelligence; machine learning; ART; embryology; semen analysis; embryo; spermatozoa; fertility; infertility; algorithm

Funding

  1. Frimedbio project
  2. Norwegian Research Council [288727]

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In recent years, there has been an exponential increase in data generated in the field of ART, with a diverse range from videos to tabular data. Artificial intelligence (AI) is progressively being used in medical practice, especially in fertility clinics, to potentially improve success rates. AI models are being developed to address the lack of objectivity in critical procedures, such as embryo and sperm assessments, but there are still challenges to overcome in order to fully utilize AI in ART.
In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively used in medical practice and may become a promising tool to improve success rates with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.

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