• Janvi Shah
• Mittal Darji
• Vinita Shah

Stroke is a serious life-threatening disease that damages the brain, just like a heart failure that damages the heart. It is third leading cause of death. Prediction of stroke is time consuming and frustrating for doctors. Chances of survival are more when treatment begins quickly. We can observe symptoms like sudden numbness or weakness within the face, arm or leg, especially on one side of the body, sudden confusion, trouble speaking, or difficulty understanding speech, sudden trouble seeing in one or both eyes. Various machine learning algorithms like SVM, RFA, DTA, Logistic Regression and KNN is employed. In this paper we have discussed about various machine learning algorithms which can be used to predict stroke. Comparative analysis of algorithms is also discussed.

Stroke prediction, Machine learning approaches, Artificial Intelligence, Random Forest.

"ROLE OF AI APPROACHES IN STROKE PREDICTION – A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.75-79, June-2022, Available :http://www.jetir.org/papers/JETIRFM06014.pdf

"ROLE OF AI APPROACHES IN STROKE PREDICTION – A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp75-79, June-2022, Available at : http://www.jetir.org/papers/JETIRFM06014.pdf