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Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0
Objective: This paper describes the state of the art, scientific publications, and ongoing research related to the methods of analysis of respiratory sounds. Methods and Material: Narrative review of the current medical and technological literature using Pubmed and personal experience. Results: We o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Carol Davila University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101681/ https://www.ncbi.nlm.nih.gov/pubmed/30140315 |
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author | Andrès, E Gass, R Charloux, A Brandt, C Hentzler, A |
author_facet | Andrès, E Gass, R Charloux, A Brandt, C Hentzler, A |
author_sort | Andrès, E |
collection | PubMed |
description | Objective: This paper describes the state of the art, scientific publications, and ongoing research related to the methods of analysis of respiratory sounds. Methods and Material: Narrative review of the current medical and technological literature using Pubmed and personal experience. Results: We outline the various techniques that are currently being used to collect auscultation sounds and provide a physical description of known pathological sounds for which automatic detection tools have been developed. Modern tools are based on artificial intelligence and techniques such as artificial neural networks, fuzzy systems, and genetic algorithms. Conclusion: The next step will consist of finding new markers to increase the efficiency of decision-aiding algorithms and tools. |
format | Online Article Text |
id | pubmed-6101681 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Carol Davila University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61016812018-08-23 Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 Andrès, E Gass, R Charloux, A Brandt, C Hentzler, A J Med Life Original Article Objective: This paper describes the state of the art, scientific publications, and ongoing research related to the methods of analysis of respiratory sounds. Methods and Material: Narrative review of the current medical and technological literature using Pubmed and personal experience. Results: We outline the various techniques that are currently being used to collect auscultation sounds and provide a physical description of known pathological sounds for which automatic detection tools have been developed. Modern tools are based on artificial intelligence and techniques such as artificial neural networks, fuzzy systems, and genetic algorithms. Conclusion: The next step will consist of finding new markers to increase the efficiency of decision-aiding algorithms and tools. Carol Davila University Press 2018 /pmc/articles/PMC6101681/ /pubmed/30140315 Text en ©Carol Davila University Press This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Original Article Andrès, E Gass, R Charloux, A Brandt, C Hentzler, A Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title | Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title_full | Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title_fullStr | Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title_full_unstemmed | Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title_short | Respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
title_sort | respiratory sound analysis in the era of evidence-based medicine and the world of medicine 2.0 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6101681/ https://www.ncbi.nlm.nih.gov/pubmed/30140315 |
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