The model organ for this research project is the best pediatric brain tumor model developed so far and can be used to test new drugs. The results of the project, conducted by the University of Trento with Bambino Gesù Children's Hospital in Rome, were published in the Nature Protocols.

Neither radiologists nor multimodal large language models (LLMs) are able to easily distinguish artificial intelligence (AI)-generated “deepfake” X-ray images from authentic ones, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA). The findings highlight the potential risks associated with AI-generated X-ray images, along with the need for tools and training to protect the integrity of medical images and prepare health care professionals to detect deepfakes.

There is a promising new drug for the rare disease mastocytosis, which is associated with skin lesions, among other things. Researchers at the University of Basel have now been able to use artificial intelligence (AI) to quantitatively measure for the first time the extent to which it reduces skin lesions.

Heart disease is the leading cause of adult death worldwide, making cardiovascular disease diagnosis and management a global health priority. An echocardiogram, or cardiac ultrasound, is one of the most commonly used imaging tools employed by physicians to diagnose a variety of heart diseases and conditions. 

As artificial intelligence (AI) becomes more common in health care, from managing records to assisting with medication decisions, researchers at the Icahn School of Medicine at Mount Sinai are asking an important question: How well does AI hold up when the workload gets intense at health system scale?

Artificial intelligence (AI) is changing the field and practice of medicine, including legal liability and the perception of who is at fault when a patient experiences harm.

“AI holds promise to improve the quality and safety of health care and to reduce errors and patient harm, but the risk of legal liability is a potential barrier for investment and development of this technology as well as the quality of care,” said Michael Bruno, professor of radiology and of medicine at Penn State College of Medicine.

Can smartphones or smartwatches help detect early signs of neurological or mental illness? Researchers at the University of Geneva (UNIGE) monitored a group of participants wearing connected devices, and used artificial intelligence to analyse data such as heart rate, physical activity, sleep and air pollution. Their findings show that connected devices can accurately predict emotional and cognitive fluctuations, opening new avenues for the early detection of changes in brain health.