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GUI System to Support Cardiology Examination Based on Explainable Regression CNN for Estimating Pulmonary Artery Wedge Pressure

Yuto OMAE, Yuki SAITO, Yohei KAKIMOTO, Daisuke FUKAMACHI, Koichi NAGASHIMA, Yasuo OKUMURA, Jun TOYOTANI

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Summary :

In this article, a GUI system is proposed to support clinical cardiology examinations. The proposed system estimates “pulmonary artery wedge pressure” based on patients' chest radiographs using an explainable regression-based convolutional neural network. The GUI system was validated by performing an effectiveness survey with 23 cardiology physicians with medical licenses. The results indicated that many physicians considered the GUI system to be effective.

Publication
IEICE TRANSACTIONS on Information Vol.E106-D No.3 pp.423-426
Publication Date
2023/03/01
Publicized
2022/12/08
Online ISSN
1745-1361
DOI
10.1587/transinf.2022EDL8059
Type of Manuscript
LETTER
Category
Biocybernetics, Neurocomputing

Authors

Yuto OMAE
  Nihon University
Yuki SAITO
  Nihon University School of Medicine
Yohei KAKIMOTO
  Nihon University
Daisuke FUKAMACHI
  Nihon University School of Medicine
Koichi NAGASHIMA
  Nihon University School of Medicine
Yasuo OKUMURA
  Nihon University School of Medicine
Jun TOYOTANI
  Nihon University

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