Ghayda, Ramy Abou, Cannarella, Rossella, Calogero, Aldo E., Shah, Rupin, Rambhatla, Amarnath, Zohdy, Wael, Kavoussi, Parviz, Avidor-Reiss, Tomer, Boitrelle, Florence, Mostafa, Taymour, and others. (2023) Artificial intelligence in andrology: From Semen Analysis to Image Diagnostics. The World Journal of Men's Health, 42 (1). ISSN 2287-4690. (doi:10.5534/wjmh.230050) (KAR id:101858)
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| Official URL: https://doi.org/10.5534/wjmh.230050 |
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Abstract
Artificial intelligence (AI) in medicine has gained a lot of momentum in the last decades and has been applied to various fields of medicine. Advances in computer science, medical informatics, robotics, and the need for personalized medicine have facilitated the role of AI in modern healthcare. Similarly, as in other fields, AI applications, such as machine learning, artificial neural networks, and deep learning, have shown great potential in andrology and reproductive medicine. AI-based tools are poised to become valuable assets with abilities to support and aid in diagnosing and treating male infertility, and in improving the accuracy of patient care. These automated, AI-based predictions may offer consistency and efficiency in terms of time and cost in infertility research and clinical management. In andrology and reproductive medicine, AI has been used for objective sperm, oocyte, and embryo selection, prediction of surgical outcomes, cost-effective assessment, development of robotic surgery, and clinical decision-making systems. In the future, better integration and implementation of AI into medicine will undoubtedly lead to pioneering evidence-based breakthroughs and the reshaping of andrology and reproductive medicine.
| Item Type: | Article |
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| DOI/Identification number: | 10.5534/wjmh.230050 |
| Uncontrolled keywords: | artificial intelligence; andrology; deep learning; diagnostic imaging; machine learning; neural networks; computer |
| Subjects: | Q Science |
| Divisions: | Divisions > Division of Natural Sciences > Biosciences |
| Funders: | University of Kent (https://ror.org/00xkeyj56) |
| SWORD Depositor: | JISC Publications Router |
| Depositing User: | JISC Publications Router |
| Date Deposited: | 29 Jun 2023 14:38 UTC |
| Last Modified: | 25 Mar 2024 12:30 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/101858 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Homa, Sheryl T..
| Creator's ORCID: |
 https://orcid.org/0000-0001-5027-0066
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