Scholarlink

Cardiovascular disease remains a leading global health concern, necessitating early detection and intervention. The proposed system introduces a wearable IoT device, combining vein-pattern recognition and continuous vital sign monitoring, backed by machine learning algorithms. Users access user-friendly personalized emergency alerts through messages and email. The system prioritizes data security and integrates seamlessly with electronic health records. As an accessible early risk assessment tool, it empowers individuals to proactively manage their heart health, facilitates timely medical intervention, and fosters a healthier society.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Ensemble Machine Learning Approaches for Early Heart Attack Detection Through IoT Devices

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Tanmay Aswale,
  • Priya Waghmare,
  • Sushma Yemmewar,
  • Vedant Choudhary,
  • Shubham Khirade

摘要

Cardiovascular disease remains a leading global health concern, necessitating early detection and intervention. The proposed system introduces a wearable IoT device, combining vein-pattern recognition and continuous vital sign monitoring, backed by machine learning algorithms. Users access user-friendly personalized emergency alerts through messages and email. The system prioritizes data security and integrates seamlessly with electronic health records. As an accessible early risk assessment tool, it empowers individuals to proactively manage their heart health, facilitates timely medical intervention, and fosters a healthier society.