Applications of Artificial Intelligence and Machine Learning Models in the Prognosis and Diagnosis of Ovarian Cancer
-
By
-
Khodeer, Dina
-
Ukozehasi, Celestin
-
Abdelmonem, Sally M.
-
April 3, 2026
-
Objective:
To review the role of AI and machine learning in enhancing the diagnosis and prognosis of ovarian cancer.
Key Findings:
- AI and radiomics improve the analysis of imaging data for ovarian cancer diagnosis.
- Radiomics can differentiate between benign and malignant tumors and predict genetic mutations.
- AI models often outperform traditional diagnostic methods in accuracy.
Interpretation:
The integration of AI and machine learning techniques in ovarian cancer diagnostics shows promise for more accurate and personalized patient care.
Limitations:
Conclusion:
AI and machine learning have the potential to significantly enhance the diagnostic and prognostic capabilities in ovarian cancer.
