A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...

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

A machine learning-driven framework accurately predicts MPA exposure and supports individualized dosing in childhood-onset LN.

Additive manufacturing (AM) has long been positioned as a disruptive force in industrial production. Its ability to enable complex geometries, accelerate design cycles, and reduce material waste has ...

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

The promise of artificial intelligence in credit scoring is undeniable. By analyzing vast, non-traditional datasets from ...

AI-driven material development and new additive manufacturing technology are accelerating new aluminum alloy, battery, and material processing innovations.

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

This activity was supported by the U.S. National Institute of Standards and Technology (Contract No. SB134117CQ0017), the Department of Energy, Los Alamos National Laboratory, and Sandia National ...

People who get less than 6 hours of sleep on weekdays have a 25% higher risk of experiencing an epiretinal membrane.