CardioPredict
A machine learning project for predicting heart attack risk levels using clinical indicators.
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Overview
CardioPredict is a machine learning project focused on predicting heart attack risk levels using clinical health indicators. The aim was to build a reliable model and turn raw health data into a more interpretable risk assessment.
Key highlights
The model achieved 98% accuracy, included feature importance analysis, and was improved through hyperparameter tuning to make predictions more stable and dependable. It reflects my interest in practical ML that balances model quality with explainability.