Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review.

Journal: International journal of medical informatics
Published Date: Dec 5, 2023

Abstract

INTRODUCTION: Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of these methods and assess their practical utility for predicting various clinical outcomes.

Authors

  • Dmitriy Viderman
    Department of Surgery, School of Medicine, Nazarbayev University, Astana, Kazakhstan; Department of Anesthesiology, Intensive Care, and Pain Medicine, National Research Oncology Center, Astana, Kazakhstan. Electronic address: dmitriy.viderman@nu.edu.kz.
  • Alexander Kotov
    Department of Computer Science, Wayne State University.
  • Maxim Popov
    Department of Computer Science, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan. Electronic address: maxim.popov@nu.edu.kz.
  • Yerkin Abdildin
    Department of Mechanical and Aerospace Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan. Electronic address: yerkin.abdildin@nu.edu.kz.

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