Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …

Motivation Medical image analysis involves a series of tasks used to assist physicians in
qualitative and quantitative analyses of lesions or anatomical structures which can …

In recent years, deep learning has been widely used in breast cancer diagnosis, and many
high-performance models have emerged. However, most of the existing deep learning …

Breast cancer is caused by the uncontrolled growth and division of cells in the breast,
whereby a mass of tissue called a tumor is created. Early detection of breast cancer can …

Breast cancer in women is the second most common cancer worldwide. Early detection of
breast cancer can reduce the risk of human life. Non-invasive techniques such as …

Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …

Histopathological image classification has become one of the most challenging tasks among
researchers due to the fine-grained variability of the disease. However, the rapid …

Introduction and Background: Despite fast developments in the medical field, histological
diagnosis is still regarded as the benchmark in cancer diagnosis. However, the input image …

Accurately determining the molecular subtypes of breast cancer is important for the
prognosis of breast cancer patients and can guide treatment selection. In this study, we …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …