Develop a ML Pipeline for Predicting Patient Risk LevelsDevelop a ML Pipeline for Predicting Patient Risk Levels
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This project involved developing a machine learning pipeline to predict patient risk levels using structured clinical data. The workflow covered data cleaning, exploratory analysis, feature preparation, model training, and risk segmentation to identify patterns associated with disease outcomes. The system was designed to support data-driven clinical decision-making by transforming raw healthcare data into interpretable patient risk insights.
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