Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualisation
Hybrid combinations of feature selection, classification and visualisation using machine learning (ham) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. Identifying a feature selection method...
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| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2021
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/28045/ |
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