This paper is in the following e-collection/theme issue:

Foundations of AI (49) Artificial Intelligence (1602) Clinical Information and Decision Making (1547) New Methods (1003) Machine Learning (1627) Tools, Programs and Algorithms (305) mHealth for Data Collection and Research (1034) Respiratory Medicine (106) Spatial Audio in XR and Spatial Computing (1)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67239, first published .
Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning–Based Audio Enhancement: Algorithm Development and Validation

Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning–Based Audio Enhancement: Algorithm Development and Validation

Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning–Based Audio Enhancement: Algorithm Development and Validation

Authors of this article:

Jing-Tong Tzeng1 Author Orcid Image ;   Jeng-Lin Li2 Author Orcid Image ;   Huan-Yu Chen2 Author Orcid Image ;   Chu-Hsiang Huang3 Author Orcid Image ;   Chi-Hsin Chen3 Author Orcid Image ;   Cheng-Yi Fan3 Author Orcid Image ;   Edward Pei-Chuan Huang3 Author Orcid Image ;   Chi-Chun Lee2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jing-Tong Tzeng   1 , BSc ;   Jeng-Lin Li   2 , PhD ;   Huan-Yu Chen   2 , PhD ;   Chu-Hsiang Huang   3 , MD ;   Chi-Hsin Chen   3 , MD ;   Cheng-Yi Fan   3 , MD ;   Edward Pei-Chuan Huang   3 * , MD ;   Chi-Chun Lee   2 * , PhD

1 College of Semiconductor Research, National Tsing Hua University, Hsinchu, Taiwan

2 Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan

3 Department of Emergency Medicine, National Taiwan University Hsin-Chu Hospital, Hsinchu, Taiwan

*these authors contributed equally

Corresponding Author:

  • Chi-Chun Lee, PhD
  • Department of Electrical Engineering
  • National Tsing Hua University
  • 101, Section 2, Kuang-Fu Road
  • Hsinchu, 300
  • Taiwan
  • Phone: 886 35162439
  • Email: cclee@ee.nthu.edu.tw