Artificial intelligence is enabling radiologists to extract valuable diagnostic information from routine chest imaging – identifying patients at risk for osteoporosis and cardiovascular disease without additional scans. At RSNA 2025, researchers presented two AI-powered tools that transform standard chest X-rays and CT scans into opportunistic screening devices.
Endometriosis affects up to one in ten women and girls of reproductive age, but for many, the path to diagnosis is both long and complex. Now, two new studies explain the diagnostic challenges in primary care.
A research team is leading the development of a sensor that paves the way for the rapid, selective and cost-effective detection of active tuberculosis infection.
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 have developed an AI model showing that it is possible to detect different neurodegenerative diseases - for example, Alzheimer’s and Lewy body disease - from a single blood sample.
Digital spatial profiling (DSP) is emerging as a powerful technology in helping specialists investigate complex kidney disease, according to a leading expert. Professor Renate Kain believes spatial profiling adds significantly to systems biology approaches that will transform diagnostic histopathology. However, she warns that the adoption and effective utilization of the technique is critically…
"Why did the computer conclude this?": Patients increasingly scrutinize the impact of AI on medical diagnostics. A new article explores the tension between transparency and legal frameworks.
A biomarker discovered in the cerebrospinal fluid could improve diagnosis of Parkinson's disease and dementia with Lewy bodies.
Bacterial infections can be difficult to distinguish from viral infections and inflammation, but a simple breath test may change that. This could reduce unnecessary antibiotic prescriptions.
At this year’s European Congress of Radiology (ECR) in Vienna, Bayer presented new data on a contrast agent that could transform MRI imaging: gadoquatrane, which requires up to 60% less gadolinium than previous standard macrocyclic preparations whilst maintaining the same diagnostic accuracy. Prof. Hubertus Pietsch, Head of MRI & CT Contrast Agent Research at Bayer and one of the key…
Pancreatic cancer remains a diagnostic challenge, due to unspecific early symptoms and lack of effective screening tools. A novel AI metabolomics platform could help overcome these issues.
Using machine learning, researchers have trained an electronic nose to detect early signs of ovarian cancer in the blood. The method could eventually be used to find many different cancers.
Clues in the CSF: Researchers have developed the first high-precision method that can theoretically diagnose common brain tumors in children and adolescents without surgery.
An AI-assisted stethoscope could help doctors identify patients with valvular heart disease who may otherwise go undiagnosed. This could reduce hospital admissions and overall healthcare costs.
Severe headache, neck pain or confusion: More than 25% of pregnant women suffering non-specific stroke symptoms sought care but were misdiagnosed, University of Pittsburgh research finds.
To better diagnose patients who appear unconscious in ICUs, and predict their recovery potential, researchers developed a tool that integrates multiple modalities for analyzing consciousness.
An international study shows that Alzheimer’s disease biomarkers can be accurately detected using simple finger-prick blood samples that can be collected at home and mailed to a laboratory.
A novel machine-learning-based solution analyses CT images and helps radiologists detect both malignant and benign lesions in the kidney more quickly and reliably.
A sample of inequality: A new study shows that AI models can infer demographic information from pathology slides, leading to bias in cancer diagnosis among different populations.
