Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, enabling researchers to process large volumes of environmental data and satellite ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Smart city initiatives are generating vast amounts of data from sensors, cameras, mobile devices, and digital service ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits, and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.

Drug development is often a long and tedious process; sometimes, taking over a decade and billions of dollars before a treatment reaches patients. In fact, over 90 per cent of drug trials fail in the ...

Overview Artificial Intelligence (AI) is a technology that allows machines to perform tasks that normally require human ...

The development of next-generation metallic materials is entering a transformative era driven by data-driven methodologies. Traditional trial-and-error ...

AI protein function prediction uses machine learning models trained on sequence and structural data to infer protein roles at ...

Quadratic regression is a classical machine learning technique to predict a single numeric value. Quadratic regression is an extension of basic linear regression. Quadratic regression can deal with ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

Intramolecular charge transfer (ICT) is one of the most important photophysical mechanisms in organic fluorophores. Among ICT processes, TICT ...