According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

While the potential benefits of AI in obesity prevention are substantial, the study devotes significant attention to ...

A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...

This special report introduces small area estimation as a modern approach for producing reliable, stand-level forest ...

While sensing technologies have advanced rapidly, the study identifies data fragmentation as one of the most persistent ...

Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...

A Hebrew University study suggests AI tools could help growers better manage water use by predicting healthy plant behavior and flagging early signs of stress.

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...