Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization

• Main Authors: Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2021
• Online Access: http://journalarticle.ukm.my/16915/1/17.pdf; http://journalarticle.ukm.my/16915/; https://www.ukm.my/jsm/malay_journals/jilid50bil3_2021/KandunganJilid50Bil3_2021.html
• Institution: Universiti Kebangsaan Malaysia

Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) 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 met...