Digitising the human embryo

Since the first successful birth from in-vitro fertilisation (IVF) in 1978, the process has improved through advances in embryo culture systems, micromanipulation, imaging, and genomics. The demographics of users of IVF are skewed in high-income settings, and people from minority ethnic groups and t...

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Bibliographic Details
Published inThe Lancet (British edition) Vol. 400; no. 10363; p. 1577
Main Authors Shafiee, Hadi, Kanakasabapathy, Manoj Kumar, Bormann, Charles L, Topol, Eric J
Format Journal Article
LanguageEnglish
Published London Elsevier Ltd 05.11.2022
Elsevier Limited
Subjects
Artificial intelligence
Clinical trials
Deep learning
Embryology
Embryos
Fertility
Fertilization
Micromanipulation
Minority & ethnic groups
Morphology
Optics
Reproductive technologies
Sperm
Womens health
United States > US
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Summary:Since the first successful birth from in-vitro fertilisation (IVF) in 1978, the process has improved through advances in embryo culture systems, micromanipulation, imaging, and genomics. The demographics of users of IVF are skewed in high-income settings, and people from minority ethnic groups and those on lower incomes are underserved. [...]the deep learning networks developed using such inequitable data are susceptible to perpetuated biases. CLB reports grants from Mass General Brigham, licence agreements with Fujifilm, consulting fees from Parity Health, lecture fees from Fujifilm, CooperSurgical, and Vitrolife, stock options in Intelon Optics (the company focuses on imaging technologies, with potential applications in AI IVF).
ISSN:0140-6736
1474-547X
DOI:10.1016/S0140-6736(22)02130-4