Artificial intelligence-based covid-19 detection using cough records

Alpaslan Gökcen, Bulut Karadaǧ, Cengiz Riva, Ali Boyaci

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)203-208
Number of pages6
JournalElectrica
Volume21
Issue number2
DOIs
StatePublished - May 2021
Externally publishedYes

Keywords

  • COVID-19
  • cough detection
  • deep learning

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