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@article{174117,
        author = {B. V S S R VASISTA and K. C N RAJU and T. RENUKA and J. L PRATAP},
        title = {HEART ATTACK DETECTION AND PREVENTION BY USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2634-2639},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174117},
        abstract = {This project proposes an integrated health monitoring system using an Arduino Uno microcontroller to collect real-time physiological data from sensors including a heartbeat sensor, GSR sensor, respiratory sensor, and temperature sensor. The system processes the sensor data and uploads it to a Python-based application for analysis, where machine learning algorithms detect abnormal patterns or outliers that could indicate potential health risks. If an anomaly is detected, the system sends an alert via a GSM module to notify the user of the abnormality. The setup combines sensor data collection, IoT data transmission, and predictive analytics for enhanced health surveillance and emergency response, with an LCD display providing real-time feedback of the sensor values for continuous monitoring.},
        keywords = {Arduino Mega, NodeMCU, GSR Sensor, Dallas Temperature Sensor, Respiratory sensor, GSM, LCD.},
        month = {March},
        }