Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System
Dublin Core
Title
Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System
Subject
COVID-19
Fuzzy C-Mean (FCM)
Propagation (BP) classification
Information Gain (IG)
Mobil Application
Description
Various mobile applications such as Mobile Health (mHealth) have been developed and spread across the world which has played an important role in mitigating the Coronavirus pandemic (COVID-19). As the COVID-19 pandemic spreads, several people have drawn parallels to influenza. While both viruses cause respiratory infections, they propagate in very different ways. This has a major impact on the public health measures that can be used to fight each virus. These viruses are pandemic-causing in the same way. That is, they both cause respiratory disease, and can present themselves in several ways, ranging from asymptomatic to severe and deadly. A proposal is presented in this paper that uses two algorithms to define and classify these pandemics, they are: The Back Propagation (BP) classification algorithm and the Fuzzy C-Mean (FCM) clustering algorithm. Two stages are implemented in the proposed system: in the first step, the FCM algorithm is used to find out the type of virus, and this algorithm is capable of handling ambiguous features of viruses. In the second step, a BP neural network is used as a classifier to detect the pandemic class. The proposed system was trained and tested using a well-known dataset (covid-19 vs influenza). Information Gain (IG) is used to optimize the related features that affect the classification process to improve speed and accuracy. The proposed mobile application is developed to support users easily detecting the COVID-19 infection by inputting the medical tests as significant features to the proposed system. The proposed system's accuracy is up to (89%), the framework was created using the Matlab programming environment and an Android Studio for Mobil application designing.
Creator
Al-zubidi, Azhar
F. AL-Bakri, Nadia
K. Hasoun, Rajaa
Hassan Hashim, Soukaena
Alrikabi, Haider Th.Salim
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 16 (2021); pp. 34-51
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2021-08-23
Rights
Copyright (c) 2021 Haider Th.Salim Alrikabi, Azhar Al-zubidi, Nadia F. AL-Bakri, Rajaa K. Hasoun, Soukaena Hassan Hashim
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Al-zubidi, Azhar et al., Mobile Application to Detect Covid-19 Pandemic by Using Classification Techniques: Proposed System, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed November 22, 2024, https://igi.indrastra.com/items/show/2080