Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …

Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …

As a subfield of machine learning, reinforcement learning (RL) aims at optimizing decision
making by using interaction samples of an agent with its environment and the potentially …

Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …

This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …

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

Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

Artificial intelligence (AI) advancements, especially deep learning, have significantly
improved medical image processing and analysis in various tasks such as disease …

Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …