Cited by 139Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

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Explainable AI for Healthcare: From Black Box to Interpretable Models

Adadi, Amina, Berrada, Mohammed·2020·Advances in Intelligent Systems and Computing

DOI 10.1007/978-981-15-0947-6_31

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“model’s capacity and limitations so that users know when and how to use the model without misuse and overtrust, especially in high-stakes domains such as healthcare (Adadi and Berrada, 2020; Merry et al., 2021; Babic et al., 2021), legal (Deeks, 2019;”
Background
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Authors: Adadi, A., & Berrada, M.
Affiliations: École Normale Supérieure de Fès (MA)
Corresponding author: Adadi, Amina
ORCID: Adadi, Amina
Berrada, Mohammed
Venue: Advances in Intelligent Systems and Computing
Publisher: Springer Singapore
Published: 2020
Pages: 327-337
ISSN: 2194-5357 (ISSN-L)
2194-5365
DOI: 10.1007/978-981-15-0947-6_31
OpenAlex: W3016087461
Cited by: 137
References: 17
Citations by year: 2026: 4 · 2025: 28 · 2024: 36 · 2023: 27 · 2022: 30 · 2021: 10 · 2020: 2
FWCI: 28.14
Type: book chapter
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Advances in intelligent systems and computing (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords: explainable AI, interpretability, black-box models, artificial intelligence in healthcare, trust in AI, transparency, clinical decision support, clinical decision-making

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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Explainable AI for Healthcare: From Black Box to Interpretable Models

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