The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

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

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

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

By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...

The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...

Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

Background Up to half of patients with infective endocarditis (IE) require cardiac surgery. Although anaemia is common, its precise prevalence, transfusion practices and impact on outcomes in ...

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 ...

Background Inflammatory bowel disease (IBD) arises from complex interactions among diet, host and gut microbiome. Although diet influences intestinal inflammation, the microbial and metabolic pathways ...

Earth system box models are essential tools for reconstructing long-term climatic and environmental evolution and uncovering ...