Doultani, Shilpa and Sharma, Prachi and Makwana, Prateek and Patil, S.P and Layek, S.S and George, L.B. and Highland, H.N. and Hadiya, K.K. (2024) AI in Reproductive Biology: Transforming Fertility Assessment, ART, and Research. Annual Research & Review in Biology, 39 (9). pp. 147-158. ISSN 2347-565X
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Abstract
Artificial Intelligence (AI) is revolutionizing reproductive biology, transforming fertility assessment, assisted reproductive technologies (ART), and research practices. This review explores AI's impact, highlighting its potential to enhance personalized care and advance scientific understanding. In fertility assessment, AI algorithms analyze vast datasets to predict treatment success, enabling clinicians to tailor personalized treatment plans. In ART, AI improves embryo selection during in vitro fertilization (IVF) by providing objective, data-driven criteria, reducing variability, and increasing success rates.AI also optimizes laboratory workflows, automating tasks such as data analysis and interpretation, enhancing efficiency, and minimizing human error. In research, AI accelerates data analysis, facilitates knowledge discovery, and enables predictive modeling, driving innovation in reproductive biology. However, AI's integration raises ethical concerns, including patient autonomy, informed consent, and data security. Collaborative efforts among stakeholders are essential to ensure responsible AI use, balancing innovation with ethical considerations. This review examines AI's transformative potential in reproductive biology, technological advancements, and the ethical landscape, envisioning a future where AI positively impacts reproductive health and clinical practice.
Item Type: | Article |
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Subjects: | Open Archive Press > Biological Science |
Depositing User: | Unnamed user with email support@openarchivepress.com |
Date Deposited: | 16 Sep 2024 07:18 |
Last Modified: | 16 Sep 2024 07:18 |
URI: | http://library.2pressrelease.co.in/id/eprint/2107 |