Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Researchers combined hyperspectral Raman imaging with machine learning to chart Alzheimer’s-related chemistry across entire ...

The research team of Weihong Tan, Xiaohong Fang, and Tao Bing from the Hangzhou Institute of Medical Sciences, Chinese Academy of Sciences, proposed a ...

Google and Microsoft's new WebMCP standard lets websites expose callable tools to AI agents through the browser — replacing costly scraping with structured function calls.

Ivan Stefanov, CEO and Co-Founder of NOTO, shares how AI, machine learning and unified platforms are reshaping financial crime prevention for institutions ...

Antiphospholipid syndrome, also known as APS, is an autoimmune disease that sits at the intersection of inflammation and blood clotting. Antiphospholipid syndrome is best known for increasing the risk ...

Rice University scientists have developed the first complete, label-free molecular atlas of the Alzheimer's brain in an ...

Hybrid human–AI models emerge as the most viable approach. In such systems, AI handles low-risk, high-frequency tasks such as ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Rice University scientists have developed the first complete, label-free molecular atlas of the Alzheimer’s brain in an ...