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  5. Differential diagnosis tool in healthcare application using respiratory sounds and convolutional neural network
 
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Differential diagnosis tool in healthcare application using respiratory sounds and convolutional neural network

Journal
Affective Computing in Healthcare: Applications based on biosignals and artificial intelligence
Date Issued
2023-08-03
Author(s)
Palaniappan R.
Sundaraj K.
Nabi F.G.
Vikneswaran Vijean
Universiti Malaysia Perlis
DOI
10.1088/978-0-7503-5182-9ch9
Handle (URI)
https://hdl.handle.net/20.500.14170/5476
Abstract
This chapter focuses on the classification of respiratory pathology using breathsound signals. The development of a computerised breath-sound analysis system could improve the standard of living of people affected by respiratory-related disease and further also be used as a differential diagnosis tool in affective computing. Accordingly, in this chapter, respiratory sounds recorded according to the Computerised Respiratory Sound Acquisition standard were obtained from subjects with respiratory sounds belonging to five different respiratory pathologies, namely, normal, wheezes, rhonchi, fine crackles, and coarse crackles.
File(s)
Research repository notification.pdf (4.4 MB)
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