A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...

In-context learning has the potential to revolutionize how machines acquire knowledge—enabling them to adapt, reason, and ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

The drug development pipeline is a costly and lengthy process. Identifying high-quality "hit" compounds-those with high potency, selectivity, and favorable metabolic properties-at the earliest stages ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

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 ...

Scientists at the University of Glasgow have harnessed a powerful supercomputer, normally used by astronomers and physicists ...

Poor data standards across government hamper scaling, says Parliament spending watchdog The UK government's Department for ...

The arrival of the 2025 NFL season means more than just making spread or total picks, as it also gives bettors the opportunity to make NFL prop bets on the league's biggest stars. From the 13 games on ...