A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to ...

Important mental health history is often present in medical records but hard to find, especially when it is missing from the ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Samuel Kaski’s two-part research lab in ELLIS Institute Finland (Probabilistic Machine Learning, Aalto University) and the Centre for AI Fundamentals in University of Manchester, is searching for ...

Depression is a highly common mental health condition that affects millions of people worldwide. Medical professionals have established that the disorder arises from a combination of biological ...

Machine learning is changing the front end of drug discovery, where researchers decide which targets to pursue and which molecules deserve costly laboratory work. Its deeper test lies further ...

Space Associates, Inc., a provider of advanced metrology and inspection solutions, announced new machine learning capabilities for its kSA Glass Breakage & Defect Detection tool. The enhancement adds ...