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This study employs time-lapse microscopy and machine learning to elucidate changes in embryonic growth kinetics with maternal aging. We analyzed morphokinetic parameters of embryos from young and aged C57BL6\/NJ mice via continuous imaging. Our findings show that aged embryos accelerated through cleavage stages (from 5-cells) to morula compared to younger counterparts, with no significant differences observed in later stages of blastulation. Unsupervised machine learning identified two distinct clusters comprising of embryos from aged or young donors. Moreover, in supervised learning, the extreme gradient boosting algorithm successfully predicted the age-related phenotype with 0.78 accuracy, 0.81 precision, and 0.83 recall following hyperparameter tuning. These results highlight two main scientific insights: maternal aging affects embryonic development pace, and artificial intelligence can differentiate between embryos from aged and young maternal mice by a non-invasive approach. Thus, machine learning can be used to identify morphokinetics phenotypes for further studies. This study has potential for future applications in selecting human embryos for embryo transfer, without or in complement with preimplantation genetic testing.<\/jats:p>","DOI":"10.1093\/biolre\/ioae056","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T04:49:05Z","timestamp":1714452545000},"page":"1115-1124","source":"Crossref","is-referenced-by-count":11,"title":["Machine learning in time-lapse imaging to differentiate embryos from young vs old mice"],"prefix":"10.1093","volume":"110","author":[{"given":"Liubin","family":"Yang","sequence":"first","affiliation":[{"name":"Division of Reproductive Endocrinology and Infertility , Department of Obstetrics and Gynecology, , Houston, Texas , USA"},{"name":"Baylor College of Medicine , Department of Obstetrics and Gynecology, , Houston, Texas , USA"},{"name":"Division of Reproductive Endocrinology and Infertility , Division of Reproductive Sciences, Department of Obstetrics, Gynecology, and Reproductive Sciences, , New Haven, Connecticut , USA"},{"name":"Yale School of Medicine , Division of Reproductive Sciences, Department of Obstetrics, Gynecology, and Reproductive Sciences, , New Haven, Connecticut , USA"},{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carolina","family":"Leynes","sequence":"additional","affiliation":[{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashley","family":"Pawelka","sequence":"additional","affiliation":[{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabel","family":"Lorenzo","sequence":"additional","affiliation":[{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Chou","sequence":"additional","affiliation":[{"name":"Pain Research , Informatics, Multi-morbidities, and Education (PRIME) Center, , West Haven, Connecticut , USA"},{"name":"VA Connecticut Healthcare System , Informatics, Multi-morbidities, and Education (PRIME) Center, , West Haven, Connecticut , USA"},{"name":"Section of Infectious Diseases , Department of Internal Medicine, , New Haven, Connecticut , USA"},{"name":"Yale School of Medicine , Department of Internal Medicine, , New Haven, Connecticut , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brendan","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason D","family":"Heaney","sequence":"additional","affiliation":[{"name":"Department of Molecular and Human Genetics, Baylor College of Medicine , Houston, Texas , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"key":"2024061704412866400_ref1","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1007\/s10815-017-0964-9","article-title":"National survey on use of time-lapse imaging systems in IVF laboratories","volume":"34","author":"Dolinko","year":"2017","journal-title":"J Assist Reprod Genet"},{"key":"2024061704412866400_ref2","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.fertnstert.2016.11.032","article-title":"One for all or all for one? 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