Paper Title
AI-Driven, Block Chain-Enabled Cardiovascular Health Management System: A Cross-Platform Predictive and Prescriptive framework

Abstract
Cardiovascular diseases are the predominant cause of fatality globally, responsible for claiming 17.9 million lives annually (World Health Organization, 2023). Despite recent developments in the healthcare industry, it still primarily remains reactive in nature, rather than preventive, leading to delayed diagnosis and higher death rates. Moreover, the absence of reliable predictive tools, AI-powered daily vitals analysis mechanisms and prompt emergency assistance systems, further aggravates the circumstances. This research paper aims to bridge this critical gap by proposing a comprehensive cross-platform cardiovascular health management system built upon the foundations of predictive and prescriptive analysis. It further incorporates a prompt emergency response mechanism that, when triggered, alerts the user’s emergency contacts about their critical condition, as well as shares the location of nearby hospitals, thus enabling rapid medical response. It aims to integrate supervised Machine learning models for predictive analysis and Blockchain-secured decentralized ledger to facilitate real-time risk assessment and secure data interoperability. It utilizes the Flutter framework to guarantee cross-platform accessibility, allowing seamless operation across different platforms. This research thus intends to accelerate the development towards transforming the cardiovascular medical landscape from reactive therapy to proactive prevention. Keywords - AI Diagnosis, Blockchain Technology, Cardiovascular disease prediction, Decentralized Storage, Flutter, Machine Learning