Real-time counting of wheezing events from lung sounds using…

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Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention

Article 2023 EN Gold

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wheeze counting algorithm. Leveraging a novel approach that includes the detailed labeling of one breathing cycle into three types: break, normal, and wheeze, this study not only identifies abnormal sounds within each breath but also captures comprehen…

16

Citations

68

References

15

Authors

2.53

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UN Sustainable Development Goals
1 SDGs
Authors & Affiliations
15 authors
#AuthorInstitutionsORCID
1 Sunghoon Im Ajou University (KR)
2 Taewi Kim Ajou University (KR)
3 Choongki Min — —
4 Sanghun Kang Ajou University (KR)
5 Yeonwook Roh Ajou University (KR)
6 Changhwan Kim Ajou University (KR)
7 Minho Kim Ajou University (KR)
8 Seung Hyun Kim Korea University (KR)
9 KyungMin Shim Seokyeong University (KR) —
10 Je‐Sung Koh Ajou University (KR)
11 Seungyong Han Ajou University (KR)
12 Jaewang Lee Eulji University (KR)
13 Dohyeong Kim Corresponding The University of Texas at Dal… (US)
14 Daeshik Kang Corresponding Ajou University (KR)
15 SungChul Seo Corresponding Seokyeong University (KR)

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