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In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm

Author

Listed:
  • Sazzli Kasim
  • Sorayya Malek
  • Cheen Song
  • Wan Azman Wan Ahmad
  • Alan Fong
  • Khairul Shafiq Ibrahim
  • Muhammad Shahreeza Safiruz
  • Firdaus Aziz
  • Jia Hui Hiew
  • Nurulain Ibrahim

Abstract

Background: Conventional risk score for predicting in-hospital mortality following Acute Coronary Syndrome (ACS) is not catered for Asian patients and requires different types of scoring algorithms for STEMI and NSTEMI patients. Objective: To derive a single algorithm using deep learning and machine learning for the prediction and identification of factors associated with in-hospital mortality in Asian patients with ACS and to compare performance to a conventional risk score. Methods: The Malaysian National Cardiovascular Disease Database (NCVD) registry, is a multi-ethnic, heterogeneous database spanning from 2006–2017. It was used for in-hospital mortality model development with 54 variables considered for patients with STEMI and Non-STEMI (NSTEMI). Mortality prediction was analyzed using feature selection methods with machine learning algorithms. Deep learning algorithm using features selected from machine learning was compared to Thrombolysis in Myocardial Infarction (TIMI) score. Results: A total of 68528 patients were included in the analysis. Deep learning models constructed using all features and selected features from machine learning resulted in higher performance than machine learning and TIMI risk score (p

Suggested Citation

  • Sazzli Kasim & Sorayya Malek & Cheen Song & Wan Azman Wan Ahmad & Alan Fong & Khairul Shafiq Ibrahim & Muhammad Shahreeza Safiruz & Firdaus Aziz & Jia Hui Hiew & Nurulain Ibrahim, 2022. "In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-28, December.
    • Handle: RePEc:plo:pone00:0278944
    DOI: 10.1371/journal.pone.0278944
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    References listed on IDEAS

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    1. Yoshua Bengio & Claude Nadeau, 1999. "Inference for the Generalization Error," CIRANO Working Papers 99s-25, CIRANO.
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    1. Sazzli Kasim & Putri Nur Fatin Amir Rudin & Sorayya Malek & Firdaus Aziz & Wan Azman Wan Ahmad & Khairul Shafiq Ibrahim & Muhammad Hanis Muhmad Hamidi & Raja Ezman Raja Shariff & Alan Yean Yip Fong & , 2024. "Data analytics approach for short- and long-term mortality prediction following acute non-ST-elevation myocardial infarction (NSTEMI) and Unstable Angina (UA) in Asians," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-28, February.

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