An Intelligent Clinical Decision Support Framework for Heart Disease Risk Prediction
This study aims to design and evaluate a Model Context Protocol–enabled Custom GPT framework that integrates ML-based predictive models with external healthcare systems to deliver context-aware, explainable, and clinically actionable heart disease risk predictions and paves the way for broader adoption of agentic AI in clinical workflows.