Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to...

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Bibliographic Details
Main Authors: Juan P. Garcia-Mendez, Amos Lal, Svetlana Herasevich, Aysun Tekin, Yuliya Pinevich, Kirill Lipatov, Hsin-Yi Wang, Shahraz Qamar, Ivan N. Ayala, Ivan Khapov, Danielle J. Gerberi, Daniel Diedrich, Brian W. Pickering, Vitaly Herasevich
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Bioengineering
Subjects:
machine learning (ML)
deep learning (DL)
electronic auscultation
lung sounds
public databases
Online Access:https://www.mdpi.com/2306-5354/10/10/1155

Internet

https://www.mdpi.com/2306-5354/10/10/1155

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