Artificial Intelligence in Gynecologic Oncology: Current Applications, Clinical Challenges, and Future Perspectives

Area of Science:

• Gynecologic Oncology
• Medical Artificial Intelligence
• Digital Pathology

Background:

• Gynecologic cancers (cervical, endometrial, ovarian, etc.) significantly impact global women's health.
• Current treatments show variable results, and diagnosis remains a challenge.

Purpose of the Study:

• To explore the application of artificial intelligence (AI) in the diagnosis and prognostication of gynecologic cancers.
• To assess the potential of multi-platform methods combining clinical and imaging data for personalized therapies.

Main Methods:

• AI has been utilized for risk prognostication in endometrial and ovarian cancers using digital pathology.
• Automated Pap smear analysis for cervical cancer detection has been developed.
• Multi-platform approaches integrating clinical and imaging data are being explored.

Main Results:

• AI demonstrates potential in risk stratification and automated diagnostics for specific gynecologic cancers.
• Combining clinical data with imaging shows promise for prognostic assessment and personalized treatment strategies.

Conclusions:

• AI offers a promising avenue for improving the diagnosis and management of gynecologic cancers.
• Addressing challenges such as data heterogeneity, ethical concerns, and algorithmic bias is crucial for clinical integration and validation.