Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Many modern technological challenges crucially depend on the properties of surfaces and interfaces. This includes the control of charge and energy transfer across electrode/electrolyte interfaces in ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Machine learning has greatly shaped the landscape of computational biology, with the integration of high-throughput data acquisition and burgeoning computational power leading to the creation of ...

Machine learning methods have found many successful applications in predicting the response variable. However, many machine ...

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 ...

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

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 ...

Researchers combined low-temperature plasma processing with machine learning to synthesize and etch 6-inch MoS2 and WS2 ...

Astronomers at the Lowell Observatory in Flagstaff are using an innovative AI technique to revolutionize how meteors are categorized.

Important mental health history is often present in medical records but hard to find, especially when it is missing from the diagnosis codes that clinicians, researchers and health systems use to ...