Transparency of Classification Systems for Clinical Decision Support

Antoine Richard, Brice Mayag, François Talbot, Alexis Tsoukiàs, Yves Meinard

Information Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15--19, 2020, Proceedings, Part III, pages 99-113, June 2020, doi: 10.1007/978-3-030-50153-2\_8

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Abstract

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.

Bibtex

@incollection{richard:hal-02890002,
  title = {Transparency of Classification Systems for Clinical Decision Support},
  author = {Richard, Antoine and Mayag, Brice and Talbot, Fran{\c c}ois and Tsouki{\`a}s, Alexis and Meinard, Yves},
  url = {https://hal.archives-ouvertes.fr/hal-02890002},
  booktitle = {Information Processing and Management of Uncertainty in Knowledge-Based Systems - 18th International Conference, IPMU 2020, Lisbon, Portugal, June 15--19, 2020, Proceedings, Part III},
  series = {Communications in Computer and Information Science},
  pages = {99-113},
  year = {2020},
  month = {June},
  doi = {10.1007/978-3-030-50153-2\_8},
  pdf = {https://hal.archives-ouvertes.fr/hal-02890002/file/manuscript.pdf},
  hal_id = {hal-02890002},
  hal_version = {v1},
  abstract = {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.}
}