ARTIFICIAL INTELLIGENCE IN GYNECOLOGICAL CARE: TRANSFORMING DIAGNOSIS, TREATMENT, AND PERSONALIZED MEDICINE
AI has brought about remarkable improvement to gynecological practice through increased diagnostic capabilities, advancement of treatment plans, and development of patient-centered health care. Advanced technology is making it easier to diagnose gynecological disorders like cervical cancer, ovarian cancer, and endometriosis through deep learning and machine learning algorithms to minimize diagnostic mistakes. In surgeries, mechanical enhancement by the aid of AI helps in timeliness, accuracy, and reduced post-surgical complications hence improved recovery. In addition, AI has been instrumental in the application of reproductive medicine through the successful enhancement of IVF, prediction of ovarian reserve, and various fertility treatments. Telemedicine solutions driven by artificial intelligence, wearable devices, and chatbots have also helped increase the availability of gynecological services in remote and underdeveloped regions. However, the gynecology patient decision-making supported by AI carries certain ethical issues such as personal data protection, distorted AI, and other factors restricting AI use and supplying a set of rules for robust usage of AI. Therefore, the impact of AI in gynecological surgery offers a promising future with enhancements to be made on the accuracy of diagnosis and surgery in addition to bespoke treatment plans for patients. Challenges such as high implementation costs and lack of staffing competent in AI use among healthcare practitioners will have to be overcome to unlock more use of AI in gynecology.
Authors
- Khalid Ali (ORCID: https://orcid.org/0000-0002-9426-4351)
- Mohamed Ashraf Ali (ORCID: https://orcid.org/0000-0003-2352-2760)
- Qosain Suriya
Institutions
- Federal University of Technology (NG)
- Dar Al-Shifa Hospital (PS)
- Federal Urdu University (PK)
- Federal Polytechnic Oko (NG)
Publication Details
- Journal
- Journal of medical & health sciences review.
- Published
- 2025-03-17
- DOI
- https://doi.org/10.62019/krgp3769
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00