University of Virginia School of Medicine scientists have developed a bold new approach to drug development and discovery that could dramatically accelerate the creation of new medicines.

UVA’s Nikolay V. Dokholyan, PhD, and colleagues have developed a suite of artificial intelligence-powered tools, called YuelDesign, YuelPocket and YuelBond, that work together to transform how new drugs are created.

AI models can generate more complete summaries of complex cancer pathology reports than physicians, according to a new Northwestern Medicine study that tested six models developed by Meta, Google, DeepSeek and Mistral AI.

The study was published in JCO Clinical Cancer Informatics, a journal from the American Society of Clinical Oncology.

A new study using an advanced “digital twin” artificial intelligence model has found that factors such as loneliness, insomnia and poor mental health substantially raise a person’s future risk of developing type 2 diabetes.

The research, led by Anglia Ruskin University (ARU) in collaboration with Cranfield University, the University of Portsmouth, and Intelligent Omics Ltd, and published in Frontiers in Digital Health, used lifestyle and health data from 19,774 UK adults in the UK Biobank, tracked for up to 17 years.

A new study maps the rapidly evolving field of intelligent colonoscopy. It argues that the next leap will come not from isolated-task modeling alone, but from generalized multimodal systems that can perceive, describe, locate, and discuss findings in clinically useful language. To move the field forward, the researchers broadly reviewed 63 datasets and 137 deep-learning models spanning classification, detection, segmentation, and vision-language tasks.

Lung cancer remains the leading cause of cancer-related deaths worldwide, accounting for nearly one in five cancer deaths - around 1.8 million lives lost each year. One of the main reasons is late diagnosis: in its early stages, the disease appears as extremely small nodules that are difficult to distinguish from healthy tissue, even for experienced radiologists.

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.