Artificial intelligence in the diagnosis and management of gynecologic cancer Journal Article
| Authors: | Paiboonborirak, C.; Abu-Rustum, N. R.; Wilailak, S. |
| Article Title: | Artificial intelligence in the diagnosis and management of gynecologic cancer |
| 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. © 2025 The Author(s). International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics. |
| Keywords: | endometrial cancer; ovarian cancer; diagnostic imaging; artificial intelligence; gynecologic oncology; early detection; cervical cancer; personalized medicine; robotic surgery |
| Journal Title: | International Journal of Gynecology and Obstetrics |
| ISSN: | 00207292 |
| Publisher: | Unknown |
| Publication status: | Online ahead of print |
| Date Published: | 2025-01-01 |
| Online Publication Date: | 2025-01-01 |
| Language: | English |
| DOI: | 10.1002/ijgo.70094 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Article -- Source: Scopus |
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