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 ...

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 ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

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 Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...