Skip to main navigation Skip to search Skip to main content

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

  • Nanyonga Aziida
  • , Sorayya Malek*
  • , Firdaus Aziz
  • , Khairul Shafiq Ibrahim
  • , Sazzli Kasim
  • *Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Fingerprint

Dive into the research topics of 'Predicting 30-day mortality after an acute coronary syndrome (acs) using machine learning methods for feature selection, classification and visualisation'. Together they form a unique fingerprint.
Sort by

Computer Science

Medicine and Dentistry

Biochemistry, Genetics and Molecular Biology

Pharmacology, Toxicology and Pharmaceutical Science

Mathematics