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AI Helps Nurses Stay One Step Ahead in Chronic Disease Care

Artificial intelligence (AI) is helping nurses better predict health problems before they become emergencies, according to a new review of existing research published in JMIR Nursing. The study found that AI-based nursing interventions can improve the care of people living with chronic illnesses by identifying patients at greater risk of complications, reducing unplanned hospital visits, and potentially lowering health care costs.

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First-of-its-Kind Computer Model of Bacterial Biofilms could Support Antibiotic Resistance Research

Faster and more effective ways to treat pseudomonas aeruginosa, a bacterium identified by the World Health Organization (WHO) as one of the most life-threatening pathogens, could be on the cards thanks to a first-of-its-kind 3D computer model developed by the University of Surrey.

The model has shown how pseudomonas aeruginosa grows and reshapes its protective layer and spreads to new surfaces.

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Testing the Limits of What's Possible (and What isn't) with AI

When can we trust the results we get from AI, and when is learning impossible? Researchers have shown that there are some problems that even the most powerful AI can reliably solve, no matter how much data it’s given.

The researchers, from the University of Cambridge and the University of California Santa Barbara, designed ‘adversarial’ mathematical systems designed to fool any AI algorithm.

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NHS to Transform Scan Access for 6.6 Million People in Major Tech Initiative

Fifteen NHS trusts across the West Midlands are a significant step closer to leveraging diagnostic expertise on a scale never seen before in the health service, after the largest digital health initiative of its kind in Europe commenced a procurement process.

Formally known as the Converged Digital Imaging Platform, the initiative will create a single diagnostic imaging record for each NHS patient in the region - helping to ensure high-quality diagnoses for patients wherever they live.

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AI in oncology drug discovery: from target identification to therapeutic molecule generation

A new review in Advanced Cancer Research explains how artificial intelligence (AI) is being used across cancer drug discovery, from finding targets to designing and testing new drug candidates. The authors show where AI is already useful, and what still needs to improve before more AI-designed therapies can reach patients.

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MEDICA and COMPAMED 2026: From Innovation to Implementation - New Topics, Formats and Networks for the Healthcare of the Future

16 - 19 November 2026, Düsseldorf, Germany.
The healthcare industry is under growing pressure to translate innovation into care more quickly and consistently. This is precisely where MEDICA and COMPAMED 2026 come in: as platforms that not only reflect trends but also enable concrete implementation. With new themes, programme formats and targeted networking opportunities, both events are driving forward the transformation process launched in 2025.

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AI in Traditional Chinese Medicine: Unraveling Herbal Medicine's Mechanisms

Rooted in thousands of years of clinical practice and holistic philosophy, Traditional Chinese Medicine (TCM) features a distinctive therapeutic model of “multicomponent, multitarget, multipathway” intervention guided by syndrome differentiation. This approach shows unique advantages in treating complex diseases including cancer, metabolic disorders, and infectious diseases. However, this inherent complexity also creates a major barrier to modern scientific interpretation:

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Doctors may Have Trouble Learning from Experience that Contradicts AI Advice

In experiments in which physicians made decisions about treating hypothetical patients, the physicians tended to trust incorrect advice presented as being generated by artificial intelligence (AI), even after given the opportunity to notice that patient recovery data contradicted the recommendations. Aranzazu Vinas of the University of the Basque Country, Spain, and colleagues present these findings in the open-access journal PLOS Digital Health.

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Meet Biomni - an AI-Powered Biomedical Co-Scientist

Researchers at Stanford University have announced the debut of Biomni - an AI-powered multi-skilled biomedical research agent. Biomni is no mere chatbot. It is a full-fledged “co-scientist” capable of designing and developing complex research workflows, said Jure Leskovec, the Alfred and Rebecca Lin Professor and professor of computer science in the School of Engineering and senior author of the paper introducing Biomni in the journal Science.

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Fighting the World's Deadliest Infection with PAC-MAN and AI

Tuberculosis, caused by the bacterium Mycobacterium tuberculosis (Mtb) is the world’s deadliest single-agent caused infection, responsible for 1.23 million deaths in 2024, according to the World Health Organization. The bacterium’s unique outer cell membrane is notoriously hard to penetrate, making few drugs, including antibiotics, effective in treating the disease.

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