Abstract
Today, pulmonary diseases are one of the major causes of mortality in the world. Even though there are different diagnostic tests available such as X-ray and tomography, the stethoscope is still the first, cheapest and the most frequently used diagnostic device for the physicians. In this paper, a smart electronic stethoscope has been designed to help physicians with the diagnosis of the disease using Machine Learning. In order to create a design that satisfies all the needs of the physicians, 15 doctors and medical students from several hospitals have been contacted and interviewed. The developed system has been tested with different machine learning techniques and its efficiency has been shown by obtaining 84% accuracy while classifying respiratory audio.
Translated title of the contribution | Diagnophone: An Electronic Stethoscope for Respiratory Audio Analysis |
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Original language | Turkish |
Title of host publication | UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 161-166 |
Number of pages | 6 |
ISBN (Electronic) | 9781728139647 |
DOIs | |
Publication status | Published - Sept 2019 |
Event | 4th International Conference on Computer Science and Engineering, UBMK 2019 - Samsun, Turkey Duration: 11 Sept 2019 → 15 Sept 2019 |
Publication series
Name | UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering |
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Conference
Conference | 4th International Conference on Computer Science and Engineering, UBMK 2019 |
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Country/Territory | Turkey |
City | Samsun |
Period | 11/09/19 → 15/09/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.