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

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

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

A highly accurate AI model improves prediabetes prediction by integrating antioxidant status with standard risk factors.

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...

Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

Machine learning models delivered the strongest performance across nearly all evaluation metrics. CHAID and CART provided the highest and most stable sensitivity, accuracy and discriminatory power, ...