Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Explanation of COVID-19 Mortality Using Artificial Neural Network Based on Underlying and Laboratory Risk Factors in Ilam, Iran

Wed Feb 28 05:19:29 2024

(2022) Explanation of COVID-19 Mortality Using Artificial Neural Network Based on Underlying and Laboratory Risk Factors in Ilam, Iran. Archives of Razi Institute. pp. 1191-1196. ISSN 03653439 (ISSN)

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The spread of new waves of coronavirus outbreaks, high mortality rates, and time-consuming and numerous challenges in achieving collective safety through vaccination and the need to prioritize the allocation of vaccines to the general population have led to the continued identification of risk factors associated with mortality in patients through innovative strategies and new statistical models. In this study, an artificial neural network (ANN) model was used to predict morbidity in patients with coronavirus disease 2019 (COVID-19). Data of 2,206 patients were extracted from the registry program of Shahid Mostafa Khomeini Hospital in Ilam, Iran, and were randomly analyzed in two training (1,544) and testing (662) groups. By fitting different models of a three-layer neural network, 12 variables could explain more than 77 of the mortality variance in COVID-19 patients. These findings could be used to better mortality management, vaccination prioritization, public education, and quarantine, and allocation of intensive care beds to reduce COVID-19 mortality. The results also confirmed the power of a better explanation of ANN models to predict the mortality of patients. Copyright © 2022 by Razi Vaccine & Serum Research Institute

Item Type: Article
Taghinezhad, F.UNSPECIFIED
Keywords: Artificial neural networks COVID-19 Iran Multilayer perceptron hemoglobin adult Article artificial neural network body mass chronic obstructive lung disease cohort analysis controlled study coronavirus disease 2019 data extraction diabetes mellitus diagnostic test accuracy study erythrocyte sedimentation rate female heart disease human hypertension intubation leukocyte major clinical study male mortality real time polymerase chain reaction receiver operating characteristic retrospective study risk factor sensitivity and specificity thrombocyte
Page Range: pp. 1191-1196
Journal or Publication Title: Archives of Razi Institute
Journal Index: Scopus
Volume: 77
Number: 3
Identification Number:
ISSN: 03653439 (ISSN)
Depositing User: مهندس مهدی شریفی

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