Heart Failure Prediction using Supervised ML/AI Technique

Heart failure is a worldwide healthy problem affecting more than 550,000 people every year.
The heterogeneity of the syndrome is reflected by its many causes and classification systems.
Machine learning has demonstrated significant potential in various medical research fields and has the potential to uncover intricate associations and the ability to identify subtypes of heart failure beyond those that are currently recognised, improve risk prediction, and ultimately pave the way for personalised medicine.
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