The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

A Marshall University – University of Missouri team has reported a web-based deep-learning platform that combines six common ...

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

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

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: Heart disease remains one of the leading causes of death worldwide. Effective management and prevention heavily depend on early detection and accurate prediction. However, traditional ...

Abstract: Over recent years, the integration of machine learning (ML) techniques within healthcare has surged, facilitating the development of predictive models to assist in disease diagnosis and ...

A common chemical that is widespread in the U.S. has been linked to an increased risk of Parkinson’s disease, researchers say. In a recent study published in the journal Neurology, researchers found a ...

A powerful new AI predicts how over 1,000 diseases may unfold across a person’s life, opening doors for precision prevention, policy planning, and bias-aware healthcare innovation. Study: Learning the ...