Computer Aided Diagnosis Systems Using Explainable AI for Digital Pathology

DOI
  • UEHARA Kazuki
    National Institute of Advanced Industrial Science and Technology (AIST)
  • SAKANASHI Hidenori
    National Institute of Advanced Industrial Science and Technology (AIST)

Bibliographic Information

Other Title
  • 病理診断支援における説明可能AI

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Description

<p>With the recent advance of deep learning technology, research of artificial intelligence (AI) applications for the medical domain has been growing. However, a lack of interpretability (or explainability) of the basis of AI decisions is a major problem for practical use of AI. Since physicians are responsible for the diagnosis, it is desirable to be able to confirm the reliability of the decisions made by AI. We developed an XAI technique to realize an AI platform, which allows co-evolve both humans and AI via interaction between them and applied it to pathological image analysis.</p>

Journal

  • Medical Imaging Technology

    Medical Imaging Technology 39 (3), 105-109, 2021-05-25

    The Japanese Society of Medical Imaging Technology

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