EurekAlert! In the Spotlight - Artificial Intelligence

Welcome to In the Spotlight, where each month we shine a light on something exciting, timely, or simply fascinating from the world of science.

This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.

Latest News Releases

Updates every hour. Last Updated: 28-May-2026 07:15 ET (28-May-2026 11:15 GMT/UTC)

27-Apr-2026

Group averages obscure how an individual’s brain controls behavior, Stanford Medicine study finds

Stanford Medicine
Peer-Reviewed Publication

Studying brain scan data from individuals — not group averages — reveals key brain-function differences in children who struggle with goal-oriented tasks, a Stanford Medicine study found.

Journal: Nature Communications

27-Apr-2026

Machine learning offers faster, more reliable analysis of Fermi surfaces

Tokyo University of Science
Peer-Reviewed Publication

Interpreting Fermi surface data requires specialized expertise and is vulnerable to noise, creating a bottleneck in materials research. Researchers now demonstrate a machine learning approach that can analyze simulated Fermi surface images of the alloy Co₂MnGa_xGe_1-xand automatically identify compositions where the Fermi surface morphology changes, even in blurred or noisy data. The method reduces the need for manual screening and could accelerate the discovery of advanced electronic materials.

Journal: Scientific Reports
Funder: Japan Science and Technology Agency, Japan Society for the Promotion of Science

27-Apr-2026

AI tool may spot adhd years before children are diagnosed

Duke University Medical Center
Peer-Reviewed Publication

In a new study, Duke Health researchers found that artificial intelligence tools can analyze routine electronic health records to accurately estimate a child’s risk of developing ADHD years before a typical diagnosis. By reviewing patterns in everyday medical data, the approach could help flag children who may benefit from earlier evaluation and follow-up.

Journal: Nature Mental Health

27-Apr-2026

Improving animal welfare in the lab: AI helps better detect pain

ETH Zurich
Peer-Reviewed Publication

Pain and welfare monitoring is essential in animal experimentation. But current assessments are subjective and often inadequate.

The new GrimACE system, developed at ETH Zurich, standardises pain and welfare monitoring in mice.

It uses computer vision and machine learning for the automated assessment of laboratory animals’ facial expressions (grimace) and posture, thereby fundamentally improving animal welfare.

Journal: Lab Animal

26-Apr-2026

Growing support for AI models in heart disease care and prevention

Flinders University
Peer-Reviewed Publication

Digital transformation and artificial intelligence (AI) in healthcare requires a range of safeguards and standards to work well, but new research from Flinders University provides support for effective AI systems to improve cardiovascular care.

The study examines how Clinical Decision Support Systems (CDSS) can transform cardiovascular disease management – a leading cause of death in Australia – by providing more accurate, timely decisions while addressing real-world barriers like workflow integration, usability and clinician adoption.

Journal: International Journal of Medical Informatics

24-Apr-2026

Physician’s medical decisions benefit from AI, Stanford Medicine-led research finds

Stanford Medicine
Peer-Reviewed Publication

A study showed that chatbots alone outperformed doctors when making nuanced clinical decisions, but when supported by artificial intelligence, doctors performed as well as the chatbots.

Journal: npj Digital Medicine

24-Apr-2026

Kent computational approach takes the guesswork out of drug development for Chagas disease

University of Kent
Peer-Reviewed Publication

Researchers at the University of Kent have established a computational protocol that could accelerate the development of more effective treatments for life-threatening parasitic infections such as Chagas disease, by enabling scientists to accurately identify reactions that can result in successful drug candidates without the need for trial and error.

Journal: ChemistryOpen
Funder: Royal Society