A social evaluation of the perceived goodness of explainability in machine learning-Reference-Cited by-同舟云学术

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A social evaluation of the perceived goodness of explainability in machine learning

Published:2021-07-25 Issue: Volume: Page:1-22
ISSN:2573-234X
Container-title:Journal of Business Analytics
language:en
Short-container-title:Journal of Business Analytics

Author:

Wanner Jonas¹,Herm Lukas-Valentin¹,Heinrich Kai²,Janiesch Christian¹³^ORCID

Affiliation:

1. Faculty of Business Management and Economics, Julius-Maximilians-Universität Würzburg, Würzburg, Germany

2. Faculty of Economics and Management, Otto-von-Guericke-Universität Magdeburg, Dresden, Germany

3. Faculty of Informatics, Hochschule Landshut, Landshut, Germany

Funder

Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Information Systems,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/2573234X.2021.1952913

Reference138 articles.

1. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

2. Support vector machines combined with feature selection for breast cancer diagnosis

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1. Recent advancements and applications of deep learning in heart failure: Α systematic review;Computers in Biology and Medicine;2024-06

2. User‐Centered Evaluation of Explainable Artificial Intelligence (XAI): A Systematic Literature Review;Human Behavior and Emerging Technologies;2024-01

3. Human Centricity in the Relationship Between Explainability and Trust in AI;IEEE Technology and Society Magazine;2023-12

4. HIEF: a holistic interpretability and explainability framework;Journal of Decision Systems;2023-05-24

5. Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability;International Journal of Information Management;2023-04

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