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

Learn how to use permutation testing to validate your machine learning models using Sklearn. This video breaks down the process to help improve model reliability and performance.

Elon Musk has spent the past year telling investors and fans that the Tesla Model Y is not just a hit, but the world’s ...

Background The National Heart Failure Audit gathers data on patients coded at discharge (or death) as having heart failure as ...

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 This study assessed whether a previously developed Monte Carlo simulation model can be reused for evaluating various strategies to minimise time-to-treatment in southwest Netherlands for ...

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

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 ...

ABSTRACT: This research evaluates the effect of monetary policy rate and exchange rate on inflation across continents using both Frequentist and Bayesian Generalized Additive Mixed Models (GAMMs).

There is often a disconnect between the intended functionality of an artificial intelligence model and its actual functionality once it's integrated into healthcare workflows. Epic has developed an ...

CU Boulder researchers apply machine learning to snow hydrology in Colorado mountain drainage basins, finding a new way to accurately predict the availability of water Determining how much water is ...