Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop

Translated title of the contribution: Diagnophone: An Electronic Stethoscope for Respiratory Audio Analysis

Ege Yag Cakir, Gokhan Ince

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 contributionDiagnophone: An Electronic Stethoscope for Respiratory Audio Analysis
Original languageTurkish
Title of host publicationUBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages161-166
Number of pages6
ISBN (Electronic)9781728139647
DOIs
Publication statusPublished - Sept 2019
Event4th International Conference on Computer Science and Engineering, UBMK 2019 - Samsun, Turkey
Duration: 11 Sept 201915 Sept 2019

Publication series

NameUBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering

Conference

Conference4th International Conference on Computer Science and Engineering, UBMK 2019
Country/TerritoryTurkey
CitySamsun
Period11/09/1915/09/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

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