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Mukherjee, H., Sreerama, P., Dhar, A., Obaidullah, S.M., Roy, K., Mahmud, M. 
ORCID: 0000-0002-2037-8348 and Santosh, K.C.,
2021.
Automatic lung health screening using respiratory sounds.
Journal of Medical Systems, 45 (2): 19.
ISSN 0148-5598
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Abstract
Significant changes have been made on audio-based technologies over years in several different fields. Healthcare is no exception. One of such avenues is health screening based on respiratory sounds. In this paper, we developed a tool to detect respiratory sounds that come from respiratory infection carrying patients. Linear Predictive Cepstral Coefficient (LPCC)-based features were used to characterize such audio clips. With Multilayer Perceptron (MLP)-based classifier, in our experiment, we achieved the highest possible accuracy of 99.22% that was tested on a publicly available respiratory sounds dataset (ICBHI17) (Rocha et al. Physiol. Meas. 40(3):035,001 20) of size 6800+ clips. In addition to other popular machine learning classifiers, our results outperformed common works that exist in the literature.
| Item Type: | Journal article | ||||||
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| Publication Title: | Journal of Medical Systems | ||||||
| Creators: | Mukherjee, H., Sreerama, P., Dhar, A., Obaidullah, S.M., Roy, K., Mahmud, M. and Santosh, K.C. | ||||||
| Publisher: | Springer Science and Business Media LLC | ||||||
| Date: | February 2021 | ||||||
| Volume: | 45 | ||||||
| Number: | 2 | ||||||
| ISSN: | 0148-5598 | ||||||
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| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Linda Sullivan | ||||||
| Date Added: | 20 Jan 2021 12:31 | ||||||
| Last Modified: | 11 Jan 2022 03:00 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/42071 |
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