Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Abstract: This study explores the predictive capacity of financial asset returns in forecasting macroeconomic regime shifts, specifically the transition among Inflation, Expansion, Stagflation, and ...

Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

Artificial intelligence has advanced rapidly, yet one area has remained consistently difficult: truly understanding human voice. Not just the words spoken, but the emotion behind them, the intent ...

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...

FedCare delivers the first visual pipeline that pinpoints, classifies and mitigates FL failures in real time, cutting convergence rounds and boosting accuracy across tested attacks without sacrificing ...