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SSM Annual Scientific Meeting
Posters
Thursday 8th September
P66 Defining the transparency, explainability, and interpretability of algorithms: a key step towards fair and just decision-making

Authors

  • Georgia D Tomova Leeds Institute of Data Analytics, University of Leeds, Leeds, UK School of Medicine, University of Leeds, Leeds, UK Alan Turing Institute, London, UK PubMed articlesGoogle scholar articles
  • Mark S Gilthorpe Leeds Institute of Data Analytics, University of Leeds, Leeds, UK School of Medicine, University of Leeds, Leeds, UK Alan Turing Institute, London, UK PubMed articlesGoogle scholar articles
  • Gabriela C Arriagada Bruneau Leeds Institute of Data Analytics, University of Leeds, Leeds, UK Inter-Disciplinary Ethics Applied Centre, University of Leeds, Leeds, UK School of Philosophy, Religion and History of Science, University of Leeds, Leeds, UK PubMed articlesGoogle scholar articles
  • Peter WG Tennant Leeds Institute of Data Analytics, University of Leeds, Leeds, UK School of Medicine, University of Leeds, Leeds, UK Alan Turing Institute, London, UK PubMed articlesGoogle scholar articles

Citation

Tomova GD, Gilthorpe MS, Arriagada Bruneau GC, et al
P66 Defining the transparency, explainability, and interpretability of algorithms: a key step towards fair and just decision-making
J Epidemiol Community Health 2022;76:A75-A76.

Publication history

  • First published August 26, 2022.
Online issue publication 
November 14, 2022

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© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.