Radiology

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.

Microwave ablation offers a potential alternative to invasive surgery for patients with the most common type of thyroid cancer, papillary thyroid carcinoma. Read more.

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.