Artificial intelligence in the diagnosis and management of gynecologic cancer
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Issued Date
2025-01-01
Resource Type
ISSN
00207292
eISSN
18793479
Scopus ID
2-s2.0-105003802550
Journal Title
International Journal of Gynecology and Obstetrics
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Gynecology and Obstetrics (2025)
Suggested Citation
Paiboonborirak C., Abu-Rustum N.R., Wilailak S. Artificial intelligence in the diagnosis and management of gynecologic cancer. International Journal of Gynecology and Obstetrics (2025). doi:10.1002/ijgo.70094 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/109981
Title
Artificial intelligence in the diagnosis and management of gynecologic cancer
Author(s)
Corresponding Author(s)
Other Contributor(s)
Abstract
Gynecologic cancers affect over 1.2 million women globally each year. Early diagnosis and effective treatment are essential for improving patient outcomes, yet traditional diagnostic methods often encounter limitations, particularly in low-resource settings. Artificial intelligence (AI) has emerged as a transformative tool that enhances accuracy and efficiency across various aspects of gynecologic oncology, including screening, diagnosis, and treatment. This review examines the current applications of AI in gynecologic cancer care, focusing on areas such as early detection, imaging, personalized treatment planning, and patient monitoring. Based on an analysis of 75 peer-reviewed articles published between 2017 and 2024, we highlight AI's contributions to cervical, ovarian, and endometrial cancer management. AI has notably improved early detection, achieving up to 95% accuracy in cervical cancer screening through AI-enhanced Pap smear analysis and colposcopy. For ovarian and endometrial cancers, AI-driven imaging and biomarker detection have enabled more personalized treatment approaches. In addition, AI tools have enhanced precision in robotic-assisted surgery and radiotherapy, and AI-based histopathology has reduced diagnostic variability. Despite these advancements, challenges such as data privacy, bias, and the need for human oversight must be addressed. The successful integration of AI into clinical practice will require careful consideration of ethical issues and a balanced approach that incorporates human expertise. Overall, AI presents significant potential to improve outcomes in gynecologic oncology, particularly in bridging healthcare gaps in resource-limited settings.