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

Background Ebstein’s anomaly (EA) exhibits significant anatomical and clinical heterogeneity, warranting a systematic ...

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 fast and accurate implementation of temperature scaling. an implementation of structured matrix scaling (SMS), a regularized version of matrix scaling that outperforms other logistic-based ...

Background: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods: Patients with T2DM who underwent ...

This project explores and evaluates multiple classification algorithms, including K-Nearest Neighbors (KNN), Logistic Regression, Support Vector Machines (SVM), and ensemble methods (Boosting and ...

Abstract: The examination of student mental health is a significant area of scholarly investigation that seeks to comprehend and address the psychological and emotional well-being of students within ...

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...