An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint
inhibitors has led to improved survival outcomes for patients with advanced-stage lung …

Lung cancer has one of the highest mortality rates of all cancers and poses a severe threat
to people's health. Therefore, diagnosing lung nodules at an early stage is crucial to …

Background Artificial intelligence (AI) in diagnostic radiology is undergoing rapid
development. Its potential utility to improve diagnostic performance for cardiopulmonary …

Tuberculosis (TB) is the leading cause of preventable death in HIV-positive patients, and yet
often remains undiagnosed and untreated. Chest x-ray is often used to assist in diagnosis …

Lung cancer is a common malignant tumor disease with high clinical disability and death
rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis …

Background Cerebral aneurysm detection is a challenging task. Deep learning may become
a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive …

Objectives To evaluate the performance of an AI-powered algorithm for the automatic
detection of pulmonary embolism (PE) on chest computed tomography pulmonary …

Lung cancer causes more deaths than breast, cervical, and colorectal cancer combined.
Nevertheless, population‐based lung cancer screening is still not considered standard …

As a promising method in artificial intelligence, deep learning has been proven successful in
several domains ranging from acoustics and images to natural language processing. With …