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ABSTRACT: Background
Artificial intelligence (AI) has significant potential in clinical practice. However, its "black box" nature can lead clinicians to question its value. The challenge is to create sufficient trust for clinicians to feel comfortable using AI, but not so much that they defer to it even when it produces results that conflict with their clinical judgment in ways that lead to incorrect decisions. Explainable AI (XAI) aims to address this by providing explanations of how AI algorithms reach their conclusions. However, it remains unclear whether such explanations foster an appropriate degree of trust to ensure the optimal use of AI in clinical practice.Objective
This study aims to systematically review and synthesize empirical evidence on the impact of XAI on clinicians'
SUBMITTER: Rosenbacke R
PROVIDER: S-EPMC11561425 | biostudies-literature | 2024 Oct
REPOSITORIES: biostudies-literature