CardioNet Insight: a Comprehensive Recommendation System for Cardiovascular Disease Prediction and Prevention through IoT Connectivity

EasyChair Preprint no. 12936

Abstract

This paper outlines the system's comprehensive approach, which integrates diverse data sources, including patient health records, real-time physiological data from wearable devices, and environmental factors. Through advanced machine learning algorithms, CardioNet Insight analyzes this data to generate personalized risk assessments for individuals, identifying potential CVD risks before they manifest clinically. Furthermore, the system provides tailored recommendations for preventive measures and lifestyle modifications, empowering users to proactively manage their cardiovascular health. By harnessing the power of IoT connectivity, CardioNet Insight represents a significant advancement in CVD management, offering a proactive and personalized approach to disease prevention and health promotion.

Keyphrases: cardio, insight, net

@Booklet{EasyChair:12936,
  author = {Julia Anderson and Nick Carter},
  title = {CardioNet Insight: a Comprehensive Recommendation System for Cardiovascular Disease Prediction and Prevention through IoT Connectivity},
  howpublished = {EasyChair Preprint no. 12936},

  year = {EasyChair, 2024}}