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

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

In this retrospective cohort analysis, researchers aimed to identify key predictors of trial enrollment among cancer patients.

When electricity or fuel powers a machine, the machine gets hotter. Finding new ways to cool machines quickly and ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

LB Beistad is a writer and musician based in Nashville, TN. Her love of gaming began with her cousin introducing her to Banjo Kazooie and Jak and Daxter. It was love at first play. Since then, she has ...

Introduction: This study aimed to develop a diabetic retinopathy (DR) Prediction model using various machine learning algorithms incorporating the novel predictor Triglyceride-glucose index (TyG).

Abstract: In the field of radio technology, the scarcity of spectrum resources has become increasingly severe, while demands for higher accuracy and speed in spectrum sensing technologies continue to ...