A Stroke is an ailment that causes harm by tearing the veins in the mind. Stroke may likewise happen when there is a stop in the bloodstream and different supplements to the mind. As per the WHO, World Health Organization, stroke is one of the world's driving reasons for death and incapacity. The majority of the work has been completed on heart stroke forecast however not many works show the gamble of a cerebrum stroke. Subsequently, the AI models are worked to foresee the chance of cerebrum stroke. The project is pointed towards distinguishing the familiarity with being in danger of stroke and its determinant factors amongst victims. The research has taken numerous factors and utilized ML calculations like Logistic Regression, Decision Tree Classification, Random Forest Classification, KNN, and SVM for accurate prediction.
Stroke; Machine learning; logistics regression; decision tree classification; random forest classification; k-nearest neighbor; support vector machine.
Priyanka Agarwal , Mudit Khandelwal , Nishtha , Dr. Amol K. Kadam "Brain Stroke Prediction using Machine Learning Approach" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 273-277
Priyanka Agarwal , Mudit Khandelwal , Nishtha , Dr. Amol K. Kadam "Brain Stroke Prediction using Machine Learning Approach" Iconic Research And Engineering Journals, 6(1)