COVID-19 detection from audio: seven grains of salt

Letter/Communication

Peer reviewed

IVAN KISKIN, Harry Coppock, Lyn Jones, Ivan Kiskin and Björn W. Schuller

The Lancet. Digital health, Vol.3(9), pp.e537-e538

01/09/2021

PMID: 34303644

Abstract

Audio event detection

Data bias

COVID-19

Artificial Intelligence

Biomedical Engineering

url

https://doi.org/10.1016/S2589-7500(21)00141-2View

Published (Version of record)

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Title: COVID-19 detection from audio: seven grains of salt
Creators: IVAN KISKIN (Author)
Harry Coppock - Department of Computer Science, Imperial College London, London, UK, SW7 2RH
Lyn Jones - Radiology Department, North Bristol NHS Trust, Bristol, UK
Ivan Kiskin - Department of Engineering Science, University of Oxford, Oxford, UK
Björn W. Schuller - Department of Computer Science, Imperial College London, London, UK, SW7 2RH
Publication Details: The Lancet. Digital health, Vol.3(9), pp.e537-e538
Publisher: Elsevier Ltd
Date published: 01/09/2021
Identifiers: 99653865502346
Academic Unit: University of Surrey
Language: English
Resource Type: Letter/Communication