Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

Objective: To understand patient portal engagement stratified by patient characteristics among adults 50 years and older with at least 1 common chronic medical condition using electronic health ...

Background: Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear ...

A modular text classification system that detects misinformation across multiple domains. Each niche has its own dataset, labeling rules, and baseline models (TF-IDF + Logistic Regression / Linear SVM ...

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 ...