Cited by 62Explainable Artificial Intelligence (XAI)Philosophy and History of ScienceEthics and Social Impacts of AI

Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare

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Durán, Juan M.·2021·Artificial Intelligence

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Crossref · 10.1016/j.artint.2021.103498

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84 of 84 references verified0 citation errors · 0 not checkable

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  • Combining explainability of algorithms with privacy-preserving methods such as federated learning might help address privacy and security implications of XAI.

    “Combining explainability of algorithms with privacy-preserving methods such as federated learning [27] might help.”

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Authors
Durán, J. M.
Affiliations
Delft University of Technology (NL)
Corresponding author
Durán, Juan M.
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
2021-08
Volume
297
Pages
103498
ISSN
0004-3702 (ISSN-L)
OpenAlex
W3137844837
Cited by
62
References
84
Citations by year
2026: 4 · 2025: 17 · 2024: 18 · 2023: 13 · 2022: 9 · 2021: 1
FWCI
3.62
Type
journal article
Language
en
Open access
Locations
Artificial Intelligence (publishedVersion)
Funders
  • European Commission
  • Netherlands Institute for Advanced Study in the Humanities and Social Sciences
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
scientific explanation, explainable AI, artificial intelligence in healthcare, health care, explanatory power, theory of explanation, explanatory relations

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