An Interpretable Model for Predicting Acute Myocardial Infarction in Distinct Patient Profiles.

Journal: Studies in health technology and informatics
Published Date: May 15, 2025

Abstract

INTRODUCTION: Acute myocardial infarction (AMI) is highly prevalent (3.8% in developed countries), affecting heterogenous populations, and can be influenced by varied factors, including demographics, clinical risk factors, and comorbidities. Identifying distinct AMI patient profiles can aid in understanding the disease and developing personalised treatment strategies.

Authors

  • Anthony Onoja
    School of Health Sciences, University of Surrey, UK.
  • Abdullah Zahid
    School of Computer Science & Electronic Engineering, University of Surrey, UK.
  • Kris Elomaa
    School of Health Sciences, University of Surrey, UK.
  • Nophar Geifman
    School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.

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