Analysis of AI Driven Brain Stroke Prediction Using Machine Learning and Deep Learning

In today's era, the convergence of modern technology and healthcare has paved the path for novel diseases prediction and prevention technologies. Brain strokes, a major public health concern around the world, necessitate accurate and prompt prediction in order to reduce their devastation. This study provides a comprehensive assessment of the literature on the use of Machine Learning (ML) and Deep Learning (DL) models in predicting of brain strokes. Through the synthesis of existing research, this paper identifies trends, best practices, and gaps in current literature, providing valuable insights for our research. Review encourages in the development of more robust, efficient, and interpretable predictive models for brain stroke prediction, thereby significantly improving patient outcomes and reducing the societal burden of this debilitating condition.