Radiology

Helping clinicians forsee surgical outcomes, a new study leveraged machine-learning algorithm for high-grade glioma patients.

A deep learning algorithm based on contrast-enhanced multiphase CT has performed well in identifying small benign renal lesions, according to new research.

Fat-enlarged axillary lymph nodes have been linked to significantly higher risks of type 2 diabetes, cardiovascular disease, and hypertension, according to new research.

New research has demonstrated that combining contrast-enhanced mammography and digital breast tomosynthesis increases early breast cancer detection amongst females with a history of the disease.

AI predicts paediatric bone growth more accurately than standard methods, revolutionizing scoliosis monitoring and improving patient care with easily scalable technology.

Researchers are using AI to improve the speed and image contrast of high-resolution eye imaging. This advancement offers clinicians a superior tool for evaluating age-related macular degeneration and other retinal diseases.

A personalised model for lung cancer screening has proven helpful for clinicians when determining how to follow up patients with pulmonary nodules identified on low-dose CT.

Mammography has been proven to be the most effective method of finding breast cancer early, when treatment is most effective. Researchers have developed a new, interpretable AI model that may be able to predict 5-year breast cancer risk from mammograms.