Evidence map›Paper›PMID 33374363›Full record

ArticleSensors (Basel, Switzerland)2020

Automatic Classification of Adventitious Respiratory Sounds: A (Un)Solved Problem?

Bruno Machado Rocha, Diogo Pessoa, Alda Marques, Paulo Carvalho, Rui Pedro Paiva

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.

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  15. Reference free auscultation quality metric and its trends.Biomedical signal processing and control · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Bruno Machado RochaUniversity of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.ORCID 0000-0003-1643-667X
Diogo PessoaUniversity of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.ORCID 0000-0002-7783-7488
Alda MarquesLab3R-Respiratory Research and Rehabilitation Laboratory, School of Health Sciences (ESSUA), University of Aveiro, 3810-193 Aveiro, Portugal.ORCID 0000-0003-4980-6200
Paulo CarvalhoUniversity of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.ORCID 0000-0002-9847-0590
Rui Pedro PaivaUniversity of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.ORCID 0000-0003-3215-3960
University of Coimbra · PTUniversity of Aveiro · PT

Funding

European Regional Development Fund POCI-01-0145-FEDER-007628-iBiMEDEuropean Regional Development Fund UID/BIM/04501/2013Fundação para a Ciência e a Tecnologia SFRH/BD/135686/2018Horizon 2020 Framework Programme 825572
6 · The paper itself

Abstract

(1) Background: Patients with respiratory conditions typically exhibit adventitious respiratory sounds (ARS), such as wheezes and crackles. ARS events have variable duration. In this work we studied the influence of event duration on automatic ARS classification, namely, how the creation of the

Indexed as

Respiratory SoundsSignal Processing, Computer-AssistedAdultAlgorithmsChildFemaleHumansMaleNeural Networks, ComputerSupport Vector Machineadventitious respiratory soundsexperimental designmachine learning

Identifiers

PMID33374363
PMCPMC7795327
OpenAlexW3115941641

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.