TY - JOUR
T1 - Artificial intelligence-based covid-19 detection using cough records
AU - Gökcen, Alpaslan
AU - Karadaǧ, Bulut
AU - Riva, Cengiz
AU - Boyaci, Ali
N1 - Publisher Copyright:
© 2021 Istanbul University. All rights reserved.
PY - 2021/5
Y1 - 2021/5
N2 - In 2019, with the emergence of coronavirus disease 2019 (COVID-19) and its spread all over the world, many people were directly affected by the pandemic. As its spread increases, it is difficult to diagnose who is actually infected. In addition to continuing vaccination studies, some technological solutions are being used to try to control the virus. One of these technological solutions is presented in this study. The disease is detected using cough data through artificial intelligence (AI). To do this, an open source data set was used from the opensigma.mit.edu website. More than 20,000 cough records representing age, gender, geographic location, and COVID-19 status are available from this site. The AI model trained on cough detection achieved 79% COVID-19 accuracy with an F1 of 80%. With the designed AI-based mobile application, COVID-19 can be detected and monitored.
AB - In 2019, with the emergence of coronavirus disease 2019 (COVID-19) and its spread all over the world, many people were directly affected by the pandemic. As its spread increases, it is difficult to diagnose who is actually infected. In addition to continuing vaccination studies, some technological solutions are being used to try to control the virus. One of these technological solutions is presented in this study. The disease is detected using cough data through artificial intelligence (AI). To do this, an open source data set was used from the opensigma.mit.edu website. More than 20,000 cough records representing age, gender, geographic location, and COVID-19 status are available from this site. The AI model trained on cough detection achieved 79% COVID-19 accuracy with an F1 of 80%. With the designed AI-based mobile application, COVID-19 can be detected and monitored.
KW - COVID-19
KW - cough detection
KW - deep learning
UR - http://www.scopus.com/inward/record.url?scp=85108873244&partnerID=8YFLogxK
U2 - 10.5152/electrica.2021.21005
DO - 10.5152/electrica.2021.21005
M3 - Article
AN - SCOPUS:85108873244
SN - 2619-9831
VL - 21
SP - 203
EP - 208
JO - Electrica
JF - Electrica
IS - 2
ER -