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May 8, 2026Expert Systems

Explainable AI in Medicine: A Comprehensive Narrative Review of Methods, Applications, and Future Directions

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Authors

HWH J WangGSGuangze ShiXLXueyu Liu

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Overview

Narrative review examines explainable AI applications in medicine, highlighting benefits and challenges for clinical trust.

Key Points

  • This review aims to explore the significance and progress of explainable AI (XAI) in improving transparency and clinical trust in medical applications.
  • Comprehensive narrative review of explainable AI methods and applications in medicine.
  • Categorization of XAI techniques into model-agnostic and model-specific approaches.
  • Analysis of clinical reliability, biases, and future research directions in XAI for medicine.
  • Highlighting the benefits of XAI, including enhanced patient–clinician communication and bias detection.
  • Identifying persistent challenges such as limited clinical deployment and inconsistent evaluation standards.
  • Emphasizing the need for rigorous validation frameworks for reliable integration into clinical workflows.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69fd7f86bfa21ec5bbf080a0https://doi.org/10.1111/exsy.70259
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