Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds

COVID-19 and heart failure (HF) are common disorders and although they share some similar symptoms, they require different treatments. Accurate diagnosis of these disorders is crucial for disease management, including patient isolation to curb infection spread of COVID-19. In this work, we aim to de...

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Autores principales:	Mehmet Ali Kobat, Tarik Kivrak, Prabal Datta Barua, Turker Tuncer, Sengul Dogan, Ru-San Tan, Edward J. Ciaccio, U. Rajendra Acharya
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 heart failure cough sounds DNA pattern advanced sound processing Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/2f0b798f7b6c44088d18d64b97de15c2
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id	oai:doaj.org-article:2f0b798f7b6c44088d18d64b97de15c2
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spelling	oai:doaj.org-article:2f0b798f7b6c44088d18d64b97de15c22021-11-25T17:20:15ZAutomated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds10.3390/diagnostics111119622075-4418https://doaj.org/article/2f0b798f7b6c44088d18d64b97de15c22021-10-01T00:00:00Zhttps://www.mdpi.com/2075-4418/11/11/1962https://doaj.org/toc/2075-4418COVID-19 and heart failure (HF) are common disorders and although they share some similar symptoms, they require different treatments. Accurate diagnosis of these disorders is crucial for disease management, including patient isolation to curb infection spread of COVID-19. In this work, we aim to develop a computer-aided diagnostic system that can accurately differentiate these three classes (normal, COVID-19 and HF) using cough sounds. A novel handcrafted model was used to classify COVID-19 vs. healthy (Case 1), HF vs. healthy (Case 2) and COVID-19 vs. HF vs. healthy (Case 3) automatically using deoxyribonucleic acid (DNA) patterns. The model was developed using the cough sounds collected from 241 COVID-19 patients, 244 HF patients, and 247 healthy subjects using a hand phone. To the best our knowledge, this is the first work to automatically classify healthy subjects, HF and COVID-19 patients using cough sounds signals. Our proposed model comprises a graph-based local feature generator (DNA pattern), an iterative maximum relevance minimum redundancy (ImRMR) iterative feature selector, with classification using the k-nearest neighbor classifier. Our proposed model attained an accuracy of 100.0%, 99.38%, and 99.49% for Case 1, Case 2, and Case 3, respectively. The developed system is completely automated and economical, and can be utilized to accurately detect COVID-19 versus HF using cough sounds.Mehmet Ali KobatTarik KivrakPrabal Datta BaruaTurker TuncerSengul DoganRu-San TanEdward J. CiaccioU. Rajendra AcharyaMDPI AGarticleCOVID-19heart failurecough soundsDNA patternadvanced sound processingMedicine (General)R5-920ENDiagnostics, Vol 11, Iss 1962, p 1962 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 heart failure cough sounds DNA pattern advanced sound processing Medicine (General) R5-920
spellingShingle	COVID-19 heart failure cough sounds DNA pattern advanced sound processing Medicine (General) R5-920 Mehmet Ali Kobat Tarik Kivrak Prabal Datta Barua Turker Tuncer Sengul Dogan Ru-San Tan Edward J. Ciaccio U. Rajendra Acharya Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
description	COVID-19 and heart failure (HF) are common disorders and although they share some similar symptoms, they require different treatments. Accurate diagnosis of these disorders is crucial for disease management, including patient isolation to curb infection spread of COVID-19. In this work, we aim to develop a computer-aided diagnostic system that can accurately differentiate these three classes (normal, COVID-19 and HF) using cough sounds. A novel handcrafted model was used to classify COVID-19 vs. healthy (Case 1), HF vs. healthy (Case 2) and COVID-19 vs. HF vs. healthy (Case 3) automatically using deoxyribonucleic acid (DNA) patterns. The model was developed using the cough sounds collected from 241 COVID-19 patients, 244 HF patients, and 247 healthy subjects using a hand phone. To the best our knowledge, this is the first work to automatically classify healthy subjects, HF and COVID-19 patients using cough sounds signals. Our proposed model comprises a graph-based local feature generator (DNA pattern), an iterative maximum relevance minimum redundancy (ImRMR) iterative feature selector, with classification using the k-nearest neighbor classifier. Our proposed model attained an accuracy of 100.0%, 99.38%, and 99.49% for Case 1, Case 2, and Case 3, respectively. The developed system is completely automated and economical, and can be utilized to accurately detect COVID-19 versus HF using cough sounds.
format	article
author	Mehmet Ali Kobat Tarik Kivrak Prabal Datta Barua Turker Tuncer Sengul Dogan Ru-San Tan Edward J. Ciaccio U. Rajendra Acharya
author_facet	Mehmet Ali Kobat Tarik Kivrak Prabal Datta Barua Turker Tuncer Sengul Dogan Ru-San Tan Edward J. Ciaccio U. Rajendra Acharya
author_sort	Mehmet Ali Kobat
title	Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
title_short	Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
title_full	Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
title_fullStr	Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
title_full_unstemmed	Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds
title_sort	automated covid-19 and heart failure detection using dna pattern technique with cough sounds
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2f0b798f7b6c44088d18d64b97de15c2
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_version_	1718412460428361728

Automated COVID-19 and Heart Failure Detection Using DNA Pattern Technique with Cough Sounds

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