Catch up on the top AI-related news and research in radiology over the past month.
Diagnostic Imaging's Advances in AI monthly roundup is your chance to catch up on the latest AI news, AI-powered imaging modalities and emerging AI research affecting the field of radiology. Review the slideshow below to see highlights from the past month.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
Can AI Facilitate Single-Phase CT Acquisition for COPD Diagnosis and Staging?
December 12th 2024The authors of a new study found that deep learning assessment of single-phase CT scans provides comparable within-one stage accuracies to multiphase CT for detecting and staging chronic obstructive pulmonary disease (COPD).
Study Shows Merits of CTA-Derived Quantitative Flow Ratio in Predicting MACE
December 11th 2024For patients with suspected or known coronary artery disease (CAD) without percutaneous coronary intervention (PCI), researchers found that those with a normal CTA-derived quantitative flow ratio (CT-QFR) had a 22 percent higher MACE-free survival rate.