Machine learning (ML) models have been increasingly used in clinical oncology for cancer diagnosis, outcome predictions, and informing oncological therapy planning. The early identification and prompt treatment of cancer, revolutionized by rapid and precise analysis of radiological and pathological images of tissues using ML algorithms, can improve the likelihood of survival and quality of care provided to cancer patients.
