The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies
Artificial intelligence (AI) has huge potential to improve the health and well-being of people, but adoption in clinical practice is still limited. Lack of transparency is identified as one of the main barriers to implementation, as clinicians should be confident the AI system can be trusted. Explainable AI has the potential to overcome this issue and can be a step towards trustworthy AI. In this paper we review the recent literature to provide guidance to researchers and practitioners on the de
Record details
Published: 10 December 2020
Source: OpenAlex
Category: Research
Topics: Healthcare · Transparency
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (10 December 2020), “The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies,” evidence record 8719, https://ethics.ai/record/8719 (originally published by OpenAlex).
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