Paper Title
Review on AI-Based Stroke Prediction System Using Linear Regression

Abstract
Stroke is one of the leading causes of mortality and long-term disability worldwide. Early prediction and prevention are critical to reducing stroke-related deaths. This research presents an AI-based stroke prediction system utilizing Linear Regression to estimate the probability of stroke occurrence based on health parameters such as age, gender, BMI, hypertension, glucose level, and lifestyle factors. The model leverages a dataset from healthcare records and employs preprocessing, feature selection, and model training to predict stroke likelihood. The results demonstrate that even with a simple regression approach, significant accuracy and interpretability can be achieved, providing a valuable tool for clinical decision-making and preventive care. Keywords - Linear Regression, Stroke Prediction, Feature Selection, Regression Approac