AI and IVF at the intersection of emerging trends; a strategic SWOT analysis harnessing opportunities and mitigating threats | ||
| Journal of Reproductive Medicine and Embryology | ||
| Article 8, Volume 1, Issue 4, February 2025, Pages 255-261 PDF (286.6 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jrme.2025.360234.1027 | ||
| Authors | ||
| Ashraf Abo Ali* 1, 2; Hesham ahmed kadry3; karim mekhimer3; Nehal Adel1, 2; Hassan Maghraby*2, 3 | ||
| 1Madina Fertility Center Madina Women Hospital, Alexandria, Egypt. | ||
| 2Egyptian Foundation of Reproductive Medicine and Embryology, Alexandria, Egypt. | ||
| 3Obstetrics and Gynecology Department, Alexandria University, Egypt. | ||
| Abstract | ||
| The integration of artificial intelligence (AI) into in vitro fertilization (IVF) laboratories marks a major step forward in reproductive medicine. AI technologies, such as machine learning and deep learning, can improve quality control (QC) and quality assurance (QA) by enhancing accuracy, consistency, and operational efficiency. These AI tools are particularly useful in automating tasks like embryo and sperm selection, reducing human error, and minimizing variability, which ultimately contributes to higher success rates in IVF treatments. However, the introduction of AI into this delicate field also brings up ethical and regulatory concerns, including issues related to data privacy and transparency in decision-making algorithms. Despite these challenges, AI holds the potential to revolutionize IVF by optimizing clinical outcomes, though it must be carefully managed to maintain ethical standards and ensure patient trust. The current article provides a SWOT analysis on the impact of AI in IVF practice and its impact on cycle outcomes. | ||
| Keywords | ||
| Fertility artificial intelligence; computer-aided diagnostics; developing countries; diagnostic imaging; machine learning; SWOT analysis | ||
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