The ability to predict wildfires - such as those that recently devastated Los Angeles and Canada - is advancing rapidly with the help of ML–driven high-quality data. A new paper, published today ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

An intelligent monitoring pipe combines optical sensing with machine learning algorithms to monitor and predict 3D soil ...

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 ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

The advertising landscape has seen a seismic shift in the recent past. Programmatic buying and real-time bidding have made ...