Please see the Editorial Comment by James S. Jelinek discussing this article. CT-based
body composition measures are well established in research settings as prognostic markers …

Radiologic tests often contain rich imaging data not relevant to the clinical indication.
Opportunistic screening refers to the practice of systematically leveraging these incidental …

Background CT-based body composition measures derived from fully automated artificial
intelligence tools are promising for opportunistic screening. However, body composition …

Purpose To develop, test, and validate a deep learning (DL) tool that improves upon a
previous feature-based CT image processing bone mineral density (BMD) algorithm and …

In addition to lung cancer, other thoracic abnormalities, such as emphysema, can be
visualized within low-dose CT scans that were initially obtained in cancer screening …

worldwide reach. Thus, it is the imaging modality best suited to address the global health
issues related to hepatic steatosis and metabolic syndrome. Although MRI (and CT) are …

Advances in Thoracic Imaging of chest radiographs. The use of deep learning to detect
pulmonary tuberculosis on chest radiographs has demonstrated high performance, with an …

Purpose To assess the cost-effectiveness and clinical efficacy of AI-assisted abdominal CT-
based opportunistic screening for atherosclerotic cardiovascular (CV) disease, osteoporosis …

Background An artificial intelligence (AI) algorithm has been developed for fully automated
body composition assessment of lung cancer screening noncontrast low-dose CT of the …

Human readers or radiologists routinely perform full-body multi-organ multi-disease
detection and diagnosis in clinical practice, while most medical AI systems are built to focus …