Predicting Heartstroke Using Machine Learning and Generative AI
Year: 2025
Type: article
Abstract: Heart strokes are among the leading causes of death and disability worldwide, with early detection being critical to reducing their impact. This project focuses on developing an AI-powered solution to predict heart stroke risks based on key health metrics, such as age, hypertension, heart disease history, BMI, glucose levels, and lifestyle factors like smoking status. The solution integrates a machine learning-based predictive system with generative AI to enhance user experience. Generative AI provides personalized health suggestions, precautions, and reminders for medication and regular checkups, empowering users to take proactive measures toward better health. The deployment framework includes FastAPI for the backend, PostgreSQL for secure data management, and an intuitive web application for user interaction. This project showcases the transformative potential of AI in healthcare, enabling early diagnosis and fostering preventive care strategies to reduce stroke incidence and improve patient outcomes. Keywords—Heart Stroke Prediction, Machine Learning, Early Diagnosis, Classification, Generative AI
DOI: 10.55041/ijsrem42846
Author: Rohit Bokam
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408741246