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Transparency of Classification Systems for Clinical Decision Support

In collaboration with the Civil Hospitals of Lyon, we aim to develop a “transparent” classification system for medical purposes. To do so, we need clear definitions and operational criteria to determine what is a “transparent” classification system in our context. However, the term “transparency” is...

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Autores principales: Richard, Antoine, Mayag, Brice, Talbot, François, Tsoukias, Alexis, Meinard, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274704/
http://dx.doi.org/10.1007/978-3-030-50153-2_8
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author Richard, Antoine
Mayag, Brice
Talbot, François
Tsoukias, Alexis
Meinard, Yves
author_facet Richard, Antoine
Mayag, Brice
Talbot, François
Tsoukias, Alexis
Meinard, Yves
author_sort Richard, Antoine
collection PubMed
description In collaboration with the Civil Hospitals of Lyon, we aim to develop a “transparent” classification system for medical purposes. To do so, we need clear definitions and operational criteria to determine what is a “transparent” classification system in our context. However, the term “transparency” is often left undefined in the literature, and there is a lack of operational criteria allowing to check whether a given algorithm deserves to be called “transparent” or not. Therefore, in this paper, we propose a definition of “transparency” for classification systems in medical contexts. We also propose several operational criteria to evaluate whether a classification system can be considered “transparent”. We apply these operational criteria to evaluate the “transparency” of several well-known classification systems.
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spelling pubmed-72747042020-06-08 Transparency of Classification Systems for Clinical Decision Support Richard, Antoine Mayag, Brice Talbot, François Tsoukias, Alexis Meinard, Yves Information Processing and Management of Uncertainty in Knowledge-Based Systems Article In collaboration with the Civil Hospitals of Lyon, we aim to develop a “transparent” classification system for medical purposes. To do so, we need clear definitions and operational criteria to determine what is a “transparent” classification system in our context. However, the term “transparency” is often left undefined in the literature, and there is a lack of operational criteria allowing to check whether a given algorithm deserves to be called “transparent” or not. Therefore, in this paper, we propose a definition of “transparency” for classification systems in medical contexts. We also propose several operational criteria to evaluate whether a classification system can be considered “transparent”. We apply these operational criteria to evaluate the “transparency” of several well-known classification systems. 2020-05-16 /pmc/articles/PMC7274704/ http://dx.doi.org/10.1007/978-3-030-50153-2_8 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Richard, Antoine
Mayag, Brice
Talbot, François
Tsoukias, Alexis
Meinard, Yves
Transparency of Classification Systems for Clinical Decision Support
title Transparency of Classification Systems for Clinical Decision Support
title_full Transparency of Classification Systems for Clinical Decision Support
title_fullStr Transparency of Classification Systems for Clinical Decision Support
title_full_unstemmed Transparency of Classification Systems for Clinical Decision Support
title_short Transparency of Classification Systems for Clinical Decision Support
title_sort transparency of classification systems for clinical decision support
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274704/
http://dx.doi.org/10.1007/978-3-030-50153-2_8
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