Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning
Abstract Auscultation has been essential part of the physical examination; this is non-invasive, real-time, and very informative. Detection of abnormal respiratory sounds with a stethoscope is important in diagnosing respiratory diseases and providing first aid. However, accurate interpretation of r...
Saved in:
Main Authors: | Yoonjoo Kim, YunKyong Hyon, Sung Soo Jung, Sunju Lee, Geon Yoo, Chaeuk Chung, Taeyoung Ha |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/350a496dc10741ddb83ca44fafc5d08c |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The use of spectrograms improves the classification of wheezes and crackles in an educational setting
by: J. C. Aviles-Solis, et al.
Published: (2020) -
Scientific Validation and Clinical Application of Lung Cancer Organoids
by: Dahye Lee, et al.
Published: (2021) -
Rhinovirus-associated wheezing in infancy Comparison with respiratory syncytial virus bronchiolitis
by: Zamorano R.,Juanita
Published: (2005) -
Abnormal Respiratory Sounds Classification Using Deep CNN Through Artificial Noise Addition
by: Rizwana Zulfiqar, et al.
Published: (2021) -
THE CORRELATION OF SYMPTOMS AND OBJECTIVE WHEEZE IN ASTHMATICS
by: Abdul Latif Khattak, et al.
Published: (2020)