报告详情
  1. 活动首页
  2. 报告清单
  3. 报告详情
Reliable AI-Powered ECG Anomaly Detection and Decision Support System for Instantaneous Medical Monitoring
编号：31 访问权限：仅限参会人 更新：2026-07-23 00:50:42 浏览：0次 In-person

报告开始：2026年07月30日 16:50（Asia/Kolkata）

报告时间：15min

所在会场：[S4] Computer Vision and Pattern Recognition [S4-3] Computer Vision and Pattern Recognition

暂无文件

摘要
Primarily in remote and resource-constrained areas, accurate and timely healthcare tracking has become crucial for the early identification of cardiac problems. The Reliable equipped with artificial intelligence ECG anomaly detection and decision support framework presented in this paper integrates XGBoost, Artificial Neural Network (ANN), simulated vital monitoring, and real-time interaction technologies. Before extracting significant statistical and morphological properties such rolling mean, variability, slope, minimum, and maximum values, ECG data from the MIT-BIH Arrhythmia Database are preprocessed to eliminate baseline drift and high-frequency noise. To increase the resilience and accuracy of classification, a hybrid ANN–XGBoost model is created. The suggested method detects ECG anomalies with 98.6% accuracy, 98.1% precision, 97.8% recall, and a 97.9% F1-score. A real-time visualization dashboard based on Streamlit and a WhatsApp alert system that uses the Twilio API to enable emergency notifications in three to five seconds are also included in the framework. The findings of the experiment show enhanced interpretability, dependability, and real-time health monitoring capabilities.
关键词
ECG anomaly detection, Reliable AI, ANN, XGBoost, IoMT, Decision Support System, Real-time healthcare monitoring, AI-enabled networks
报告人
RAJESWARI P
Research Scholar ANNA UNIVERSITY

稿件作者
RAJESWARI P ANNA UNIVERSITY
发表评论
验证码 看不清楚，更换一张
全部评论
重要日期

  • 会议日期

    07月30日

    2026

    至

    08月01日

    2026

  • 06月30日 2026

    初稿截稿日期

  • 07月30日 2026

    注册截止日期

主办单位
The United Societies of Science
承办单位
Kongunadu College of Engineering and Technology
协办单位
IEEE Section
IEEE Madras Section
联系方式
登录查看完整联系方式
历届会议
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询