However, a decision taken by the company earlier in 2024 underlined how researchers in sectors like drug discovery see the importance of the tool by triggering the creation of multiple workalikes ...

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...

Researchers at Trinity College Dublin have found that a machine learning model could help clinicians predict which people with depression are more likely to improve with digital cognitive behavioral ...

Dao is part of a central group that provides data and machine-learning capabilities to the company. He ensures the data team has the right tools to complete their work. He also aims to make it easy ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as well?

Researchers at the Department of Energy's SLAC National Accelerator Laboratory and collaborating institutions recently built a generative AI model that can recreate molecular structures from the ...

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

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 ...

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.

Abstract: Epileptic seizures impair patients’ health and quality of life, and electroencephalography (EEG)-based prediction enables timely intervention. Early work on epileptic seizure prediction ...