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

doi:10.1587/transinf.2022EDL8059

Regular Section

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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Keywords: pulmonary artery wedge pressure, cardiology examination, convolutional neural network, regression activation map

JOURNAL FREE ACCESS

2023 Volume E106.D Issue 3 Pages 423-426

DOI https://doi.org/10.1587/transinf.2022EDL8059

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Abstract

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.

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