Histopathologic basis of a deep learning pelvic computed tomography model for prognostic prediction among patients with advanced high-grade serous ovarian carcinoma

Key Points

• The deep learning model effectively extracts histopathological features from CT images, making prognostic predictions possible.
• With accurate extraction from imaging, the model enhances the ability to predict outcomes in patients with high-grade serous ovarian carcinoma.
• Analysis focuses on the deep learning approach, assessing its performance using advanced image processing techniques.
• These findings highlight the potential for integrating advanced imaging with machine learning to improve prognostic models in cancer care.

Abstract