A review of evaluation approaches for explainable AI with applications in cardiology
Ahmed M. Salih,
Ilaria Boscolo Galazzo,
Polyxeni Gkontra
et al.
Abstract:Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI models and is important in building trust in model predictions. XAI explanations themselves require evaluation as to accuracy and reasonableness and in the context of use of the underlying AI model. This review details the evaluation of XAI in cardiac AI applications and has found that, of the studies examined, 37% evaluated XAI quality using literature results, 11% used clinicians as domain-experts, 11% used proxies… Show more
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