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Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review.

Qian XuWenzhao XieBolin LiaoChao HuLu QinZhengzijin YangHuan XiongYi LyuYue ZhouAijing Luo
Published in: Journal of healthcare engineering (2023)
The review explores the meaning of the interpretability of CDSS and summarizes the current methods for improving interpretability from technological and medical perspectives. The results contribute to the understanding of the interpretability of CDSS based on AI in health care. Future studies should focus on establishing formalism for defining interpretability, identifying the properties of interpretability, and developing an appropriate and objective metric for interpretability; in addition, the user's demand for interpretability and how to express and provide explanations are also the directions for future research.
Keyphrases
  • artificial intelligence
  • healthcare
  • clinical decision support
  • machine learning
  • big data
  • deep learning
  • current status
  • electronic health record
  • palliative care