From hospital leaflets to spoken answers in dozens of languages, new research from the University of East London (UEL) suggests artificial intelligence (AI) could dramatically improve how patients learn about serious eye conditions.

A research team led by UEL’s Dr Mohammad Hossein Amirhosseini and Dr Fatima Kalabi from Queen’s Hospital in London, in collaboration with Moorfields Eye Hospital in London, and Inselspital University Hospital of Bern in Switzerland, has developed a multilingual, voice-enabled AI chatbot designed to help people understand retinal detachment

Accurate diagnosis in pediatric care can be particularly challenging, especially when rare diseases present with subtle or overlapping symptoms. Early uncertainty in diagnosis may delay treatment and increase the risk of complications. While artificial intelligence (AI) has shown potential in healthcare, most previous studies have relied on simplified or curated cases rather than real-world clinical data.

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?