Researchers from Intermountain Healthcare and Stanford University say 10 seconds is about how quickly a new system they studied that utilizes artificial intelligence (AI) took to accurately identify key findings in chest X-rays of patients in the emergency department suspected of having pneumonia.

Researchers at the University of Arizona Health Sciences are seeking a new and more accurate way to diagnose breast cancer and contribute to improved outcomes for patients worldwide.

For the first time, a sophisticated computer model has been shown to accurately predict two of the most challenging side effects associated with radiation therapy for head and neck cancer. This precision oncology approach has the potential to better identify patients who might benefit from early interventions that may help to prevent significant weight loss after treatment or reduce the need for feeding tube placement. Findings were presented at the 61st Annual Meeting of the American Society for Radiation Oncology (ASTRO), Sept. 15-18, 2019, in Chicago.

Digital medical technology company Brainlab unveiled Loop-X, which it calls the first mobile intraoperative imaging robot, at the 2019 North American Spine Society annual meeting (NASS 2019), Sept. 25-28 in Chicago.