Clinically Relevant Sound-Based Features in COVID-19 Identification: Robustness Assessment With a Data-Centric Machine Learning Pipeline-Reference-Cited by-同舟云学术

Clinically Relevant Sound-Based Features in COVID-19 Identification: Robustness Assessment With a Data-Centric Machine Learning Pipeline

Published:2022 Issue: Volume:10 Page:105149-105168
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Matias Pedro¹^ORCID,Costa Joao¹,Carreiro Andre V.¹^ORCID,Gamboa Hugo¹^ORCID,Sousa Ines¹^ORCID,Gomez Pedro²,Sousa Joana³^ORCID,Neuparth Nuno⁴^ORCID,Carreiro-Martins Pedro⁴^ORCID,Soares Filipe¹^ORCID

Affiliation:

1. Fraunhofer Portugal AICOS–Porto, Porto, Portugal

2. NeuSpeLab, CTB, Universidad Politécnica de Madrid, Madrid, Spain

3. NOS Inovação, Campo Grande, Lisbon, Portugal

4. Comprehensive Health Research Center (CHRC), NOVA Medical School, Lisbon, Portugal

Funder

ConnectedHealth

OSCAR

Competitiveness and Internationalisation Operational Programme

Lisbon Regional Operational Programme

PORTUGAL 2020 Partnership Agreement

European Regional Development Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09906975.pdf?arnumber=9906975

Reference56 articles.

1. The voice of COVID-19: Acoustic correlates of infection in sustained vowels

2. Cough Sound Analysis Can Rapidly Diagnose Childhood Pneumonia

3. Clinical, laboratory, and imaging features of pediatric COVID-19

4. Overview: Systemic Inflammatory Response Derived From Lung Injury Caused by SARS-CoV-2 Infection Explains Severe Outcomes in COVID-19

5. Analysis of the Cough Sound: an Overview

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