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This research article discusses the application of quantum-enhanced machine learning techniques for heart failure detection, comparing their performance to traditional machine learning methods. The study demonstrates that quantum algorithms, particularly the quantum random forest classifier, achieve higher accuracy and efficiency in detecting heart failure using a dataset with 14 attributes. The findings highlight the potential of quantum computing in improving healthcare outcomes through advanced data anal

Author

AMIT KUMAR

Language

EN