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.
Reading an LLM-generated recap to get the gist of a scientific publication? Not a good idea, a new study finds: Most leading chatbots exaggerate the findings – prompting for more accuracy even makes things worse.
Researchers evaluated the clinical value of using ChatGPT to interpret seizure semiology in order to predict which brain areas to remove to achieve seizure freedom in epilepsy patients.
A new AI tool called PERISCOPE should help healthcare providers determine which patients need extra monitoring to protect them from wound or lung infections, UTIs or sepsis.
A novel deep-learning approach automatically finds and classifies microcalcifications found in mammography images—bringing both accuracy and consistency to breast-cancer screening.
Results of a new retrospective study demonstrate the potential of a novel, CT-based deep learning-driven tool to enhance liver cancer diagnosis, treatment planning, and response evaluation.
Using AI to analyse ultrasound scans can detect up to 35% more risk pregnancies than scans performed by healthcare professionals without AI decision support, according to new results.
Multiple sclerosis often transitions from a relapsing-remitting to secondary progressive form, which requires different treatment. Now, an AI model can determine this change with 90% certainty.
Pupil dilation and involuntary facial movements could provide a window into diagnosing tinnitus. A new method uses AI to detect minuscule reactions to various sounds and noises.
Using AI and extensive analyses of gene activity in tumours, researchers have found new, precise biomarkers to diagnose prostate cancer at an early stage through a simple urine sample.
Dutch researchers have developed an AI tool to support Mohs surgery, a precise but time-consuming procedure to treat the most common form of cancer in the Netherlands: basal cell carcinoma.
GPs may soon be able to identify patients with an increased risk of lung cancer up to 4 months earlier with an algorithm created by researchers based on the data of more than half a million patients.
Breast MRI has emerged as a powerful diagnostic tool, particularly for women with dense breast tissue where traditional mammography faces limitations. In her presentation at ECR 2025, radiographer Hanna Kalliomäki highlighted several technological advances transforming breast cancer detection and diagnosis. From time-saving abbreviated protocols and AI-assisted analysis to contrast-free…
Despite their improving diagnostic accuracy, medical AI systems are often met with skepticism by radiologists. Their patients, however, seem more inclined to embrace this technology, a study shows.
Researchers have developed an AI tool that creates synthetic yet medically accurate models of fibrotic heart tissue (heart scarring), aiding treatment planning for atrial fibrillation (AF) patients.
While generative AI shows immense potential for healthcare, a critical reliability issue lurks beneath the surface: LLMs don't think like doctors do, a data science expert explained at the Emerging Technologies in Medicine (ETIM) congress in Essen. This potentially fatal flaw, however, may be fixable, he suggested.
Despite previous global declines, pulmonary tuberculosis (TB) is on the rise again. A new AI-powered lung ultrasound shows promise in improving diagnostic performance of TB.
A new AI tool can extract key information from brain MRI scans of multiple sclerosis (MS) patients. This could be used to improve disease and treatment response monitoring.
A network of artificial neurons imitating the human brain could help identify patients at risk of a serious arrhythmia from an ECG and avoid many cases of sudden cardiac death, a new study suggests.
The evolving role of AI tools in digital pathology was explored at an open discussion during the annual Digital Pathology and AI Congress in London with a high-level panel of practitioners looking at current and future technology options. The panel of pathologists, scientists and academics from Europe and the USA assessed the tools they currently use and are available to them, and those they…
