Diagnosis of COVID-19 disease based on a modified convolutional neural network on the example of lung X-rays

Jamil Alsayaydeh, Jamil Abedalrahim and Fedorchenko, Ievgen and Oliinyk, Andrii O. and Stepanenko, Aleksandr and Fedoronchak, Tetiana and Korniienko, Serhii and Chornobuk, Maksym (2023) Diagnosis of COVID-19 disease based on a modified convolutional neural network on the example of lung X-rays. ARPN Journal Of Engineering And Applied Sciences, 18 (11). pp. 1337-1344. ISSN 1819-6608

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Abstract

As a result of the study, a machine learning model based on a modified convolutional neural network was developed to diagnose COVID-19 lesions from lung X-rays. Due to the improvement of the network architecture, it was possible to obtain a classification accuracy of 91%. The developed model can be used in the field of health care to assist medical staff in the analysis of X-rays, which will reduce the likelihood of medical error.

Item Type:	Article
Uncontrolled Keywords:	Pattern recognition, COVID-19, Classification, Neural network, Perceptron
Divisions:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	23 Jun 2025 01:53
Last Modified:	23 Jun 2025 01:53
URI:	http://eprints.utem.edu.my/id/eprint/28757
Statistic Details:	View Download Statistic

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