AI Powered Stroke Prediction and Prevention System Using NLP

This system offers an advanced solution for stroke prediction by combining Artificial Intelligence (AI) and Natural Language Processing (NLP) to enhance early detection and prevention. It analyses structured health data, including medical records and wearable vitals, alongside unstructured data from clinical notes, patient reports, and online health forums. Advanced machine learning techniques such as Random Forest and Gradient Boosting are applied for accurate stroke risk prediction. NLP methods like Named Entity Recognition (NER) and sentiment analysis extract valuable insights from unstructured medical text. The model delivers personalized prevention strategies, including lifestyle changes, dietary recommendations, and early medical intervention. Real-time alert mechanisms are also integrated to detect warning signs and initiate emergency responses. This system helps prevent strokes by enabling timely risk detection, improving patient care, and supporting early, personalized treatment decisions using AI-driven insights. Key Words: Stroke prediction, Artificial Intelligence (AI), Natural Language Processing (NLP), Early detection, Random Forest, Gradient Boosting, Named Entity Recognition (NER), Personalized prevention.