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Subject Visually interpretable deep network for diagnosis (by Seong Tae Kim) is accepted in Physics in Medicine and Biology
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Date 2018-11-07
Visually interpretable deep network has been accepted as regular paper in Physics in Medicine and Biology.

The title is "Visually interpretable deep network for diagnosis of breast masses on mammograms". The paper contribution is to propose new visual interpretable deep network for doctors to understand why diagnosis deep network predicts a malignancy decision. The visual interpretation based on doctor's medical description, is indeed very needed to give strong confidence in the deep learning based CAD.
This paper has been written by Seong Tae Kim, Jae-Hyeok Lee, and Hakmin Lee, and Yong Man Ro.