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Can artificial intelligence predict COVID-19 mortality?

A C Genc1, D Cekic, K Issever

  • 1Department of Internal Medicine, Faculty of Medicine, Sakarya University, Sakarya, Turkey. selcukyaylaci@sakarya.edu.tr.

European Review for Medical and Pharmacological Sciences
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Summary

Artificial intelligence (AI) can predict COVID-19 patient mortality in the intensive care unit (ICU) using initial laboratory data. This AI model achieved high accuracy, aiding in pandemic management strategies.

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Area of Science:

  • Medical Informatics
  • Epidemiology
  • Intensive Care Medicine

Background:

  • COVID-19 pandemic necessitated advanced predictive tools for patient outcomes.
  • Artificial intelligence (AI) offers potential for analyzing complex patient data.

Purpose of the Study:

  • To develop and validate an AI model for predicting mortality in intensive care unit (ICU) patients with COVID-19.

Main Methods:

  • Utilized 589 ICU patient records, analyzing 90 parameters.
  • Identified 9 key parameters influencing mortality.
  • Trained an AI model on 471 patients and validated on 118 patients.

Main Results:

  • The AI model demonstrated 83% sensitivity, 84% specificity, and 84% accuracy.
  • Achieved an F1 score of 0.81 and an area under the curve (AUC) of 0.91.
  • Early-onset laboratory parameters effectively predicted COVID-19 patient mortality.

Conclusions:

  • AI models can accurately predict COVID-19 mortality in ICU settings.
  • Findings highlight AI's utility in pandemic management and clinical decision-making.