A deep learning approach for predicting outcomes of triple-negative breast cancer
Breast cancer is the most common cancer in women. Triple-negative breast cancer affects 10-20% of breast cancer patients and is associated with an especially bad prognosis. Today, tissue slides are assessed manually by a clinician to set a prognosis. However, the prediction of outcomes could possibly be improved using machine learning. This work investigates various machine learning techniques for
