Electronic patient records, diagnostic values, study cohorts: data management has become a central component in healthcare - in diagnostics and therapy as well as in medical research.
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.
Data experts have created the first global carbon analytics database – a new resource to help hospitals and clinics save money, reduce waste, improve patient care, and tackle climate change.
Computational pathology is becoming increasingly important in helping deliver precision medicine to a wider range of patients. Experts at the 37th European Congress of Pathology in Vienna discussed how algorithms can optimise laboratory workflows, generate stronger evidence for molecular tumour boards, and enhance clinical trial design.
Integrating the patient’s voice: A new study shows access to patient-reported outcome (PRO) data improves the consistency of the evaluation of treatment-related side effects in patients with cancer.
Stroke patients in four NHS hospitals are now receiving genetic tests that determine whether a commonly prescribed drug will work for them – a breakthrough that could transform treatment for millions. Digital approaches are spearheading a drive to help make genomic medicine part of everyday care. The role of digital tools was a central theme at the HETT (Healthcare Excellence Through…
Digital transformation, including AI, is key to improving healthcare services - but this may be easier said than done: A new UK study identifies hurdles for AI implementation in NHS hospitals.
From identifying under-utilized rooms to tracking spare mobile equipment like wheelchairs, spatial awareness technology is evolving to improve day-to-day operations on healthcare sites. The technology, which is already being deployed in airports, universities and industrial premises, is now seeing growing applications within hospitals. At the HETT (Healthcare Excellence Through Technology) North…
A new study shows that retrieval-augmented generation (RAG) can eliminate hallucinations in clinical large language models (LLMs) while protecting patient privacy during contrast media consultations.
The Pharmaceutical Automation and Digitalisation Congress (AUTOMA+) 2025 welcomes delegates to be a part of its 5th anniversary in Vösendorf, Austria on 24-25 November. This edition focuses on AI-powered pharma, robotics and smart digital solutions.
If data used to train AI models for medical applications differs from the real-world data, it could lead to patient harm. A new study found proactive strategies to mitigate such data shifts.
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.
The new national Precision Omics Initiative Sweden (PROMISE) aims to generate and integrate extensive molecular data to create a model for precision medicine implementation for Sweden.
MRI is an essential tool for clinicians, but the variability of image acquisition protocols is a challenge for achieving consistent and reliable interpretation. A new study intends to fix this issue.
The boom in interventional radiology procedures has enabled great strides in ischemic stroke management. But while a myriad of techniques are available, the challenge remains in choosing the most appropriate thrombectomy treatment on the spot, according to Jordi Blasco Andaluz, a neuroradiologist at Hospital Clinic Barcelona. The new ROSSETTI registry is designed to change this.
A survey found that many Americans use a device to monitor their heart, but few share that data with their doctor. Cardiologists explain when findings should be discussed with a medical professional.
Anyone who has exchanged a few lines of dialogue with a large language model (LLM), will probably agree that generative AI is an impressive new breed of technology. LLMs show great potential in addressing some of the most urgent challenges in healthcare. At the Medica tradefair, several expert sessions were dedicated to generative AI, its potential medical applications and current caveats.
Can an AI determine whether or not a person drinks beer by looking at their knee X-rays? It can't – but the claim shows why “shortcut learning” is such a dangerous mechanism in medical AI.
In the world of theatre, the ‘deus ex machina’, the god from the machine, is a dramaturgical trick to resolve seemingly unsolvable conflicts. Can artificial intelligence (AI) also be such a universal problem solver for internal medicine? At the Annual Congress of the German Society of Internal Medicine (DGIM), Dr Isabella Wiest explored the potential – and limitations – of AI helpers.
A new study investigating the impact of AI in healthcare shows that using LLMs to process thousands of patient records daily across multiple hospitals could lead to substantial resource consumption.
