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<p>The rapid growth of clinical explainable AI (XAI) models raised concerns over unclear purposes and false hope regarding explanations. Currently, no standardised metrics exist for XAI evaluation. We developed a clinician-informed, 14-item checklist including clinical, machine and decision attributes. This is the first step toward XAI standardisation and transparent reporting XAI methods to enhance trust, reduce risks, foster AI adoption, and improve decisions to determine the true clinical potential of applied XAI.</p>

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Clinician-informed XAI evaluation checklist with metrics (CLIX-M) for AI-powered clinical decision support systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月14日

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  • Aida Brankovic,
  • David Cook,
  • Jessica Rahman,
  • Alana Delaforce,
  • Jane Li,
  • Farah Magrabi,
  • Federico Cabitza,
  • Enrico Coiera,
  • DanaKai Bradford

摘要

The rapid growth of clinical explainable AI (XAI) models raised concerns over unclear purposes and false hope regarding explanations. Currently, no standardised metrics exist for XAI evaluation. We developed a clinician-informed, 14-item checklist including clinical, machine and decision attributes. This is the first step toward XAI standardisation and transparent reporting XAI methods to enhance trust, reduce risks, foster AI adoption, and improve decisions to determine the true clinical potential of applied XAI.