New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

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

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...

AI scenario planning doesn’t attempt to be “right” in the traditional forecasting sense. Its real value lies in systematic ...

The research was supported by the National Science Foundation, State of Minnesota Weather Ready Extension, and Minnesota Pollution Control Agency. The research was done in collaboration with the ...

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 ...

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

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.

Trading autonomously, in real time, at a scale no human desk can match. Right now, an algorithm is reading macro signals, analysing sentiment, and executing positions before an analyst finishes their ...

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 ...

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