A new multi-omics AI model combines cfDNA and cfRNA to predict preterm birth risk with nearly 90% accuracy, offering promising insights for maternal health.
If technology seeks to transform oncology practice, it must solve three big needs: data, training and trust. Annemiek Snoeckx, Co-Chair of the Digital Health Network at the European Cancer Organisation, explains.
Surabhi Srivastava, Commercial Head UK and EU at Qure.ai, discusses how integrating artificial intelligence can reduce chest X-ray reporting times and accelerate early lung cancer diagnosis.
Europe is seeing a surge in AI-powered healthcare innovation, with startups leading the charge in transforming patient care, diagnostics, and treatment.
Yasir Ahmad and Moneeza Baig from the College of Electrical and Mechanical Engineering unpack AI in academia, arguing that it is time to de-learn and re-learn.
Researchers have shown that AI can detect early laryngeal cancer and related lesions from voice recordings, offering a simple, non-invasive screening option.
A new artificial intelligence tool is helping researchers tackle some challenges within fusion energy by protecting the inside of fusion reactors from the intense heat of plasma.
Researchers from the University of Zurich have developed an AI-driven gene editing method that improves DNA repair predictions, enabling more accurate and safer genome modifications.
King's College London researchers develop a minimally invasive under-the-skin electrode that allows continuous, real-world tracking of epilepsy seizures, improving diagnosis and treatment options.
Scientists from the U.S. Department of Energy’s Argonne National Laboratory have been honoured with the 2025 Royal Society of Chemistry’s Materials Chemistry Horizon Prize.
University Hospital Southampton is implementing Aiforia’s PD-L1 lung cancer AI solution to assess PD-L1 staining in lung cancer specimens. Dr Vipul Foria and Dr Victoria Elliot describe their journey so far.
A research team from Chiba University and its collaborators has developed a fully numerical, machine learning-based design method that significantly enhances the stability and efficiency of wireless power transfer (WPT) systems.
Stanford researchers have developed an AI-powered "virtual scientist" capable of designing drug and vaccine candidates, marking a leap forward in biomedical research.
With the global demand for clean, sustainable energy continuing to intensify, scientists are starting to use innovative technology to help fast-track the transition: AI-powered digital twins.
