The first Europe-wide expert working group on Artificial Intelligence in mental health launches today to the ECNP congress in Munich, where the group will host an open discussion, setting out the potential, the problems, and possible directions for AI in psychiatry and neuroscience. Going forward, the group will set out plans to guide the regulation and development of artificial intelligence (AI) in mental health in Europe.

WashU won a federal grant to build AI models that will help scientists better understand aerosol effects on marine low clouds.

A research “super team” co-led by the Buck Institute for Research on Aging and Georgetown University has received an award of up to $51.7 million from the Advanced Research Projects Agency for Health (ARPA-H) to predict how disease-causing proteins misfold before irreversible damage occurs and use those predictions to develop novel diagnostics and treatments. The four-year effort is expected to lead to new ways of detecting, slowing and treating neurodegenerative diseases and cancer, with an initial focus on Alzheimer's disease and Ewing sarcoma.

The study, “IDP-T5CKNN: A Protein Language Model for Prediction of Intrinsically Disordered Proteins,” was carried out by Deepak Chaurasiya in Current Computer Science.

A researcher at the Indian Institute of Information Technology, Allahabad, has developed a new lightweight computational method for identifying the flexible, structurally unpredictable regions of proteins that are linked to cancer, cardiovascular disease, and neurodegeneration, and has shown that it outperforms over 20 existing tools on a standard benchmark, without requiring the heavy computing power that state-of-the-art deep learning methods demand.

Founded in 2014 by Alex Zhavoronkov, PhD, Founder and Co-CEO of Insilico Medicine, ARDD made its North American debut in Boston following years of growth in Europe. What began as an academically focused scientific gathering has evolved into a global forum connecting fundamental aging biology with the computational power, industrial capabilities, and investment needed to advance a new generation of longevity technologies.