Medical decision making increasingly relies on machine learning algorithms to analyze
complex patient data and provide recommendations. However, the lack of interpretability in …

Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …

The paper addresses the challenge of imbalanced classification in the context of
cerebrovascular diseases, including stroke, transient ischemic attack (TIA), and vascular …

Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory
diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide …

Background Stroke is the leading worldwide cause of disability and death. Effective stroke
prevention and management depend on early identification of stroke risk. Methods Eight …

Stroke prediction remains a critical area of research in healthcare, aiming to enhance early
intervention and patient care strategies. This study investigates the efficacy of machine …

This article provides a machine learning-based drug categorization research effort. The
public repository Kaggle is where the dataset for this study was obtained. Age, sex, blood …

Stroke presents a formidable global health threat, carrying significant risks and challenges.
Timely intervention and improved outcomes hinge on the integration of Explainable Artificial …

Abstrac Background and Aims Stroke is one of the most common causes of death
worldwide, leading to numerous complications and significantly diminishing the quality of life …