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Transparency of Classification Systems for Clinical Decision Support

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Date
2020
Link to item file
https://hal.archives-ouvertes.fr/hal-02890002
Dewey
Programmation, logiciels, organisation des données
Sujet
Explainable AI; Transparency of Algorithms; Health Information Systems; Multi-label Classification
DOI
http://dx.doi.org/10.1007/978-3-030-50153-2_8
Conference name
Information Processing and Management of Uncertainty in Knowledge-Based Systems. 18th International Conference, IPMU 2020
Conference date
2020
Author
Lesot, M.-J., Vieira, S., Reformat, M.
Publisher
Springer
URI
https://basepub.dauphine.fr/handle/123456789/21082
Collections
  • LAMSADE : Publications
Metadata
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Author
Richard, Antoine
Mayag, Brice
Talbot, François
Tsoukiàs, Alexis
Meinard, Yves
Type
Communication / Conférence
Item number of pages
99-113
Abstract (EN)
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 "transpar-ent". We apply these operational criteria to evaluate the "transparency" of several well-known classification systems.

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