Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Preeclampsia with severe features remains a dangerous threat during pregnancy—especially in low-resource settings like ...

Exercise training is a cornerstone of cardiac rehabilitation (CR) for patients with coronary artery disease (CAD), and ...

Fourteen-year-old Zeynep Demirbas tested four AI models on 3,553 Reddit posts to see how accurately they could detect stress.

Methane-munching microbes in soil might be more important than previously thought, a new study finds. Soil is an important ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

An 18-year-old student from Palo Alto has developed a model that could help tackle ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Financial institutions need model risk management software that can discover hidden spreadsheets and EUCs, govern formal statistical and ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...