Stroke Prediction

Stroke prevention methods were explored because strokes are the leading cause of death in Canada and the number of deaths is expected to grow over the next decade.As a solution to this problem, a model was created to predict a person's risk of having a stroke based on their physical traits and lifestyles.Current models that use facial recognition to detect strokes provide certain benefits but are less desirable than the proposed stroke prediction model as they can not detect strokes before they happen.The team utilized a multilayer perceptron model on data containing attributes such as gender, blood pressure, and BMI (body mass index) to predict a person's likelihood of stroke.The model was able to achieve 96% accuracy on testing data.