Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...

Scholars analyze how the use of machine learning could reshape EPA drinking water standards.

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 ...

Predicting solar activity is crucial for understanding and mitigating its effects on the heliosphere, particularly with regard to Earth and its surrounding ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

Abstract: Osteoarthritis (OA) is the most prevalent form of arthritis, commonly affecting the knee joint and characterized by the progressive degeneration of articular cartilage (AC). Among the ...

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

This issue of The Journal of Risk Model Validation features two papers that directly address validation using machine learning. Whether their findings imply we will all (including the editor) become ...

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

Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant ...