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Authors: Guilherme Campos 1 and João Quintas 2

Affiliations: 1 Telecomunicações e Informática (DETI) – Universidade de Aveiro (UA) and Instituto de Engenharia Electrónica e Informática de Aveiro (IEETA) – Universidade de Aveiro (UA), Portugal ; 2 Instituto de Sistemas e Robótica (ISR) – Instituto Superior Técnico (IST), Portugal

Keyword(s): Adventitious Lung Sounds, Automatic Detection Algorithms, Annotation, Agreement, Performance Metrics, Validation.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Data Engineering ; Databases and Datawarehousing ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Pattern Recognition and Machine Learning ; Society, e-Business and e-Government ; Software Systems in Medicine ; Web Information Systems and Technologies

Abstract: The development of computerised diagnosis tools based on lung auscultation necessitates appropriate validation. So far, this work front has received insufficient attention from researchers; validation studies found in the literature are largely flawed. We believe that building open-access crowd-sourced information systems based on large-scale repositories of respiratory sound files is an essential task and should be urgently addressed. Most diagnosis tools are based on automatic adventitious lung sound (ALS) detection algorithms. The gold standards required to assess their performance can only be obtained by human expert annotation of a statistically significant set of respiratory sound files; given the inevitable subjectivity of the process, statistical agreement criteria must be applied to multiple independent annotations obtained for each file. For these reasons, the information systems we propose should provide simple, efficient annotation tools; facilitate the formation of credi ble annotation panels; apply appropriate agreement criteria and metrics to generate goldstandard ALS annotation files and, based on them, allow easy quantitative assessment of detection algorithm performance. (More)

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Paper citation in several formats:
Campos, G. and Quintas, J. (2015). On the Validation of Computerised Lung Auscultation. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF; ISBN 978-989-758-068-0; ISSN 2184-4305, SciTePress, pages 654-658. DOI: 10.5220/0005293406540658

@conference{healthinf15,
author={Guilherme Campos. and João Quintas.},
title={On the Validation of Computerised Lung Auscultation},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF},
year={2015},
pages={654-658},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005293406540658},
isbn={978-989-758-068-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2015) - HEALTHINF
TI - On the Validation of Computerised Lung Auscultation
SN - 978-989-758-068-0
IS - 2184-4305
AU - Campos, G.
AU - Quintas, J.
PY - 2015
SP - 654
EP - 658
DO - 10.5220/0005293406540658
PB - SciTePress