AI is revolutionizing gynecologic cancer care (cervical, ovarian, endometrial) by improving early detection, diagnosis, and treatment planning. Machine learning (ML) and deep learning (DL) enhance screening accuracy, automate workflows, and integrate complex clinical data, addressing gaps in traditional methods and increasing efficiency in EHR management and clinical trial enrollment.
In screening, AI enables automated Pap smear analysis and AI-guided colposcopy for cervical cancer, high-accuracy ultrasound models and ctDNA liquid biopsies for ovarian cancer (AUC = 0.94), and neural network–based risk prediction for endometrial cancer, guiding recurrence monitoring and chemotherapy decisions.
For diagnosis and treatment, AI-driven radiomics extracts quantitative MRI/CT data, while DL models automate tumor segmentation. Histopathology AI classifies slides with up to 97% accuracy and predicts mutations like BRCA. AI also improves robotic surgery precision, 3D preoperative planning, adaptive radiotherapy, and chemotherapy response prediction, enabling truly personalized gynecologic cancer care.