Traditional machine learning models for automatic information classification require retraining data for each task. Researchers have demonstrated that art data can be automatically classified with ...

The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the literature to understand the clinical implications of ...

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 ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

Researchers developed a two-stage machine learning framework that detected diabetes and classified records as prediabetes, ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...

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 ...