With the help of artificial intelligence, computers are to simulate human thought processes. Machine learning is intended to support almost all medical specialties. But what is going on inside an AI algorithm, what are its decisions based on? Can you even entrust a medical diagnosis to a machine? Clarifying these questions remains a central aspect of AI research and development.
FLock.io has been spotlighted by the World Economic Forum (WEF)’s MINDS programme for two NHS trusts using its privacy-preserving AI to tackle major diseases. Both trusts use its federated learning platform to train clinical models while maintaining 100% data sovereignty.
Researchers have developed an AI technology that analyzes daily activity and environmental data from older adults to identify digital behavioral markers of cerebrovascular disease risk at home.
A multicenter randomized clinical trial shows that real-time AI-assisted colonoscopy significantly improves adenoma detection among individuals at high risk for colorectal cancer.
Will artificial intelligence (AI) render radiologists obsolete? What seemed a likely scenario only nine years ago, has now given way to a quite different reality: At RSNA 2025, two experts outlined how AI tools are becoming essential allies – not replacements – for radiologists facing an unprecedented workforce crisis.
Why do patients discontinue their medication? Using large language models, researchers analysed medical records to assess the most common reasons. This could help better understand treatment pathways.
Will surgeons be replaced by machines in the future? With the rising impact of AI and robotics, this concern is on the minds of many medical professionals and patients alike. At the 2026 German Surgery Congress, Prof. Dr Jörg-Peter Ritz, President of the German Society for General and Visceral Surgery (DGAV) and Chief Physician and Medical Director at Helios Kliniken Schwerin, painted a more…
AI models can now assess breast cancer risk directly from changes in screening mammograms over time, a new study shows. This opens the door to a new era of dynamic breast cancer risk assessment.
AI is transforming the way cancer is diagnosed and treated. Dr Yuri Tolkach shared his group's advances in developing AI-based tools for oncological pathology at the DPAI Europe congress.
"Let's book you in": AI chatbots are generally seen as a welcome tool for managing medical screening appointments. However, too much of a good thing can backfire, a new study finds.
Improved detection of clinical errors and time-saving on the one hand, inadequate training on the other: the latest Future Health Index points out benefits and challenges of medical AI integration.
A new AI model enables more efficient analysis of tissue samples taken from colorectal cancer tumours. This can help shorten diagnosis times, reduce costs, and improve diagnostic accuracy.
A new AI-based method can reduce the time required for certain MRI brain scans by up to 90% while maintaining a high level of accuracy, paving the way for more efficient and accessible neuroimaging.
A team of researchers has developed an AI system capable of interpreting some of the most complex heart scans in medicine, cardiac MRI, without the need for manually labeled training data.
Researchers have discovered that teaching Large Language Models (LLMs) to mimic human intuition and reasoning significantly improves their ability to provide accurate medical care-seeking advice.
Discussion at the Pharmaceutical Automation and Digitalisation Congress (AUTOMA+) 2026 recognises that artificial intelligence is an important part of clinical innovation, positioning it as a practical tool for improving speed, decision accuracy and transparency in drug development. Industry attention is increasingly shifting towards AI-driven data ecosystems, advanced analytics and intelligent…
A new study using a “digital twin” AI 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.
AI models can generate more complete summaries of complex cancer pathology reports than physicians, according to a new study that tested six models developed by Meta, Google, DeepSeek and Mistral AI.
To improve lung cancer detection, researchers have developed a new AI system that employs a dual approach to analyse CT scans – seeing both detail and context at the same time.
Researchers are developing a portable AI-powered scanning slit-light device, designed to make ophthalmic care more accessible, so patients can be assessed any place, and any time.
