Automated detection of abnormal respiratory sound from electronic stethoscope and mobile phone using MobileNetV2

Author:

Liao Ximing,Wu Yin,Jiang Nana,Sun Jiaxing,Xu Wujian,Gao Shaoyong,Wang Jun,Li TingORCID,Wang Kun,Li QiangORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Biomedical Engineering

Reference42 articles.

1. Fundamentals of lung auscultation;Bohadana;N Engl J Med,2014

2. Everard ML, Hadjileontiadis LJ, Priftis KN. Breath Sounds : From Basic Science to Clinical Practice. 1st ed. Cham: Springer International Publishing : Imprint: Springer,; 2018. p. 1 online resource (VIII, 319 pages 79 illustrations, 63 illustrations in color.

3. Analysis of respiratory sounds: state of the art;Reichert;Clin Med Circ Respirat Pulm Med,2008

4. Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning;Kim;Sci Rep,2021

5. Wheezes, crackles and rhonchi: simplifying description of lung sounds increases the agreement on their classification: a study of 12 physicians' classification of lung sounds from video recordings;Melbye;BMJ OpenRespir Res,2016

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