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

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Title: Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.
Authors: Im, Sunghoon1 (AUTHOR), Kim, Taewi1 (AUTHOR), Min, Choongki2 (AUTHOR), Kang, Sanghun1 (AUTHOR), Roh, Yeonwook1 (AUTHOR), Kim, Changhwan1 (AUTHOR), Kim, Minho1 (AUTHOR), Kim, Seung Hyun3 (AUTHOR), Shim, KyungMin4 (AUTHOR), Koh, Je-sung1 (AUTHOR), Han, Seungyong1 (AUTHOR), Lee, JaeWang5 (AUTHOR), Kim, Dohyeong6 (AUTHOR) dohyeong.kim@utdallas.edu, Kang, Daeshik1 (AUTHOR) dohyeong.kim@utdallas.edu, Seo, SungChul7 (AUTHOR) dohyeong.kim@utdallas.edu
Source: PLoS ONE. 11/20/2023, Vol. 18 Issue 11, p1-18. 18p.
Database: Academic Search Ultimate
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  Data: Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 11/20/2023, Vol. 18 Issue 11, p1-18. 18p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=173719857
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