Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop

Ege Yag Cakir; Gokhan Ince

doi:10.1109/UBMK.2019.8907227

Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop

Ege Yag Cakir
, Gokhan Ince

Bilgisayar Mühendisliği Bölümü

Istanbul Technical University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

Özet

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.

Tercüme edilen katkı başlığı	Diagnophone: An Electronic Stethoscope for Respiratory Audio Analysis
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	161-166
Sayfa sayısı	6
ISBN (Elektronik)	9781728139647
DOI'lar	https://doi.org/10.1109/UBMK.2019.8907227
Yayın durumu	Yayınlandı - Eyl 2019
Etkinlik	4th International Conference on Computer Science and Engineering, UBMK 2019 - Samsun, Türkiye Süre: 11 Eyl 2019 → 15 Eyl 2019

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	4th International Conference on Computer Science and Engineering, UBMK 2019
Ülke/Bölge	Türkiye
Şehir	Samsun
Periyot	11/09/19 → 15/09/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

Keywords

AdaBoost
Audio Processing
CNN
Human Computer Interaction
KNN
Machine Learning
SVM
Signal Processing

Belgeye Erişim

10.1109/UBMK.2019.8907227

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Cakir, E. Y., & Ince, G. (2019). Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop. In UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering (pp. 161-166). Makale 8907227 (UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UBMK.2019.8907227

@inproceedings{551d82153c284fb4a594f20232440dbf,

title = "Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop",

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.",

keywords = "AdaBoost, Audio Processing, CNN, Human Computer Interaction, KNN, Machine Learning, SVM, Signal Processing",

author = "Cakir, \{Ege Yag\} and Gokhan Ince",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 4th International Conference on Computer Science and Engineering, UBMK 2019 ; Conference date: 11-09-2019 Through 15-09-2019",

year = "2019",

month = sep,

doi = "10.1109/UBMK.2019.8907227",

language = "T{\"u}rk{\c c}e",

series = "UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "161--166",

booktitle = "UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering",

address = "United States",

}

Cakir, EY & Ince, G 2019, Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop. in UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering., 8907227, UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering, Institute of Electrical and Electronics Engineers Inc., pp. 161-166, 4th International Conference on Computer Science and Engineering, UBMK 2019, Samsun, Türkiye, 11/09/19. https://doi.org/10.1109/UBMK.2019.8907227

Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop. / Cakir, Ege Yag; Ince, Gokhan.
UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering. Institute of Electrical and Electronics Engineers Inc., 2019. p. 161-166 8907227 (UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Diagnophone

T2 - 4th International Conference on Computer Science and Engineering, UBMK 2019

AU - Cakir, Ege Yag

AU - Ince, Gokhan

PY - 2019/9

Y1 - 2019/9

N2 - 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.

AB - 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.

KW - AdaBoost

KW - Audio Processing

KW - CNN

KW - Human Computer Interaction

KW - KNN

KW - Machine Learning

KW - SVM

KW - Signal Processing

UR - https://www.scopus.com/pages/publications/85076215371

U2 - 10.1109/UBMK.2019.8907227

DO - 10.1109/UBMK.2019.8907227

M3 - Konferans katkısı

AN - SCOPUS:85076215371

T3 - UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering

SP - 161

EP - 166

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

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 11 September 2019 through 15 September 2019

ER -

Cakir EY, Ince G. Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop. In UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering. Institute of Electrical and Electronics Engineers Inc. 2019. p. 161-166. 8907227. (UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering). doi: 10.1109/UBMK.2019.8907227

Diagnophone: Solunum Sesi Analizi Ǐin Bir Elektronik Stetoskop

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap