Artificial intelligence in ivf laboratories elevating outcomes through precision and efficiency

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dc.contributor.authorHew, Yaling
dc.contributor.authorKütük, Duygu
dc.contributor.authorDüzcü, Tuba
dc.contributor.authorErgün, Yağmur
dc.contributor.authorBaşar, Murat
dc.date.accessioned2026-01-07T11:20:44Z
dc.date.available2026-01-07T11:20:44Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, Sağlık Bilimleri Fakültesi, Sağlık Yönetimi Bölümü
dc.description.abstractIncorporating artificial intelligence (AI) into in vitro fertilization (IVF) laboratories signifies a significant advancement in reproductive medicine. AI technologies, such as neural networks, deep learning, and machine learning, promise to enhance quality control (QC) and quality assurance (QA) through increased accuracy, consistency, and operational efficiency. This comprehensive review examines the effects of AI on IVF laboratories, focusing on its role in automating processes such as embryo and sperm selection, optimizing clinical outcomes, and reducing human error. AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. However, integrating AI also brings ethical, regulatory, and societal challenges, including concerns about data security, algorithmic bias, and the human–machine interface in clinical decision-making. Through an in-depth examination of current case studies, advancements, and future directions, this manuscript highlights how AI can revolutionize IVF by standardizing processes, improving patient outcomes, and advancing the precision of reproductive medicine. It underscores the necessity of ongoing research and ethical oversight to ensure fair and transparent applications in this sensitive field, assuring the responsible use of AI in reproductive medicine.
dc.identifier.citationHew, Y., Kütük, D., Düzcü, T., Ergün, Y. ve Başar, M. (2024). Artificial intelligence in ivf laboratories elevating outcomes through precision and efficiency. Biology, 13(12). http://dx.doi.org/10.3390/biology13120988
dc.identifier.doi10.3390/biology13120988
dc.identifier.issn2079-7737
dc.identifier.issue12
dc.identifier.pmid39765654
dc.identifier.scopus2-s2.0-85213232850
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.3390/biology13120988
dc.identifier.urihttps://hdl.handle.net/20.500.12511/13356
dc.identifier.volume13
dc.identifier.wosWOS:001387108200001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorDüzcü, Tuba
dc.institutionauthorid0000-0002-4108-535X
dc.language.isoen
dc.relation.ispartofBiology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial Intelligence
dc.subjectIVF Laboratory
dc.subjectOutcomes
dc.subjectQuality Assurance
dc.subjectQuality Control
dc.titleArtificial intelligence in ivf laboratories elevating outcomes through precision and efficiency
dc.typeOther

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