Object With the development of deep learning, the number of training samples for medical
image-based diagnosis and treatment models is increasing. Generative Adversarial …

Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

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 …

There has been an explosive growth in research over the last decade exploring machine
learning techniques for analyzing chest X-ray (CXR) images for screening cardiopulmonary …

Anomaly detection has become an indispensable tool for modern society, applied in a wide
range of applications, from detecting fraudulent transactions to malignant brain tumors. Over …

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a
pandemic resulting in over 2.7 million infected individuals and over 190,000 deaths and …

Pneumonia is an infamous life‐threatening lung bacterial or viral infection. The latest viral
infection endangering the lives of many people worldwide is the severe acute respiratory …

In medical image classification tasks, it is common to find that the number of normal samples
far exceeds the number of abnormal samples. In such class-imbalanced situations, reliable …

Purpose Convolutional neural networks (CNNs) have rapidly emerged as one of the most
promising artificial intelligence methods in the field of medical and dental research. CNNs …

Computer-aided detection (CADe) systems have been actively researched for polyp
detection in colonoscopy. To be an effective system, it is important to detect additional …