International Journal on Science and Technology

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Patient Alert System To Predict And Alert Cardiovascular Disease Risk

Author(s) Saranya D, Karthikeyan S
Country India
Abstract This project uses the Random Forest algorithm to predict heart disease risk based on key health data. Using the Cleveland heart disease dataset and chi-square feature selection, the model achieved 88.5% accuracy. It also provides real-time alerts with patient location, aiding timely medical response and better decision-making.
Keywords Heart disease, Machine learning, Random Forest, Risk prediction, Cleveland dataset, Chi-square test, Real-time alert, Medical diagnosis, Healthcare, Classification.
Field Computer
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-06-08
DOI https://doi.org/10.71097/IJSAT.v16.i2.5978
Short DOI https://doi.org/g9pz66
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