Radiology

An artificial intelligence system for humeral tumour detection has been developed, and can be applied to chest radiographs to evaluate impact on reader performance. Read more.

A new research aims to determine the upstaging rates of digital breast tomosynthesis detected radial scars with and without atypia, and to identify features relating to upstaging risk. Read now.

Researchers have developed a natural language processing based model, which utilises information from radiology reports to accurately identify patients with suspected pulmonary embolism in the emergency department.

Researchers at Johns Hopkins University, Baltimore, Maryland, USA, have investigated muscle loss as a risk factor of heart failure, emphasising the underexplored association between thigh muscle measurements and heart failure.

Deep learning methods have the potential to improve clinical strategies for addressing ultrasound Breast imaging-reporting and data system 4A lesions, according to recent research.

New research has shown that CT may be the preferred method for treating obstructive coronary artery disease in younger patients, being less invasive than ICA.

Artificial intelligence was an integral part of this year’s European Congress of Radiology, in Vienna, Austria, and this was showcased in a captivating plenary lecture, on the second day of Congress.

New research suggests that annual breast cancer screening starting at age 40 years, and continuing to age 79 or older, results in the highest reduction in mortality with minimal risks.