lorenzodenisi/Heart-Failure-Clinical-Records
Analisys of the dataset Heart Failures clinical records from UCI using different rebalancing techiniques and different models
This project helps medical researchers and data scientists predict patient survival after heart failure using clinical records. It takes patient data like age, blood pressure, and other clinical measurements, applies various data balancing and machine learning techniques, and outputs predictions about whether a patient will survive. This is designed for professionals in healthcare analytics or medical research.
No commits in the last 6 months.
Use this if you need to analyze heart failure patient data to identify survival patterns and risk factors using machine learning models.
Not ideal if you are a clinician looking for real-time diagnostic tools or personalized treatment recommendations.
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Last pushed
Sep 14, 2020
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