Objective: This study aims to develop an explainable machine learning model, incorporating stacking techniques, to predict the occurrence of liver injury in patients with sepsis and provide decision ...

Machine learning operations (MLOps) have rapidly evolved from experimental workflows to production-critical systems powering everything from fraud detection to autonomous vehicles. But as ...

The arrival of the 2025 NFL season means more than just making spread or total picks, as it also gives bettors the opportunity to make NFL prop bets on the league's biggest stars. From the 13 games on ...

The Kansas City Chiefs and Los Angeles Chargers renew their AFC West rivalry when they meet in the 2025 NFL Sao Paulo Game on Friday. Kickoff at Corinthians Arena is scheduled for 8 p.m. ET. This ...

Researchers from Edith Cowan University (ECU) are developing an artificial intelligence algorithm that can use bone density scans captured to detect potential spine fractures to estimate visceral fat ...

Learning disorders are common, yet most teachers and parents are unaware of their impact on one’s life, work and academic journey. In the old days of caning and corporal punishments in our schools, ...

Objective: To develop and validate a real-world evidence-driven early warning system for the risk-stratified prediction of coronavirus disease 2019 (COVID-19)-associated hepatic dysfunction in ...

When models attempt to get their way or become overly accommodating to the user, it can mean trouble for enterprises. That is why it’s essential that, in addition to performance evaluations, ...

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...

Abstract: In this letter, we propose the B-GHF framework, an end-to-end collision state inference method based on a Bayesian framework that does not rely on external force/torque (F/T) sensors in the ...