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Medikal Uygulamalar için Ses Bulut Platformu

  • Hasan Can Aydan*
  • , Meral Korkmaz
  • , Beyza Cizmeci
  • , Ismail Kocak
  • , Nilufer Egrican
  • , Gokhan Ince
  • *Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

The usability and health of a person's voice has dire impact on the person's quality of life. Pathological issues that may exist on a person's voice often cannot be detected by a regular listener. Medical attention from a professional may be necessary to detect vocal pathologies. Analysis of the patients complaints and a perceptual evaluation performed by a doctor is one of the most common ways to diagnose a vocal condition. This method can be invasive, time consuming and expensive. Features of the voice can be extracted and utilized in a computer environment to make the same diagnosis which may increase the speed and accuracy of the diagnosis and decrease the cost. In this paper, a cloud application which collects vocal data in a database is proposed. With data mining and machine learning methods, a new tool has been developed to detect and diagnose vocal anomalies in patients. The effectiveness of the suggested platform has been demonstrated with a pathological detection and recognition application running in the server.

Tercüme edilen katkı başlığıVoice cloud platform for medical applications
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2017 25th Signal Processing and Communications Applications Conference, SIU 2017
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781509064946
DOI'lar
Yayın durumuYayınlandı - 27 Haz 2017
Etkinlik25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Süre: 15 May 201718 May 2017

Yayın serisi

Adı2017 25th Signal Processing and Communications Applications Conference, SIU 2017

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???event.eventtypes.event.conference???25th Signal Processing and Communications Applications Conference, SIU 2017
Ülke/BölgeTurkey
ŞehirAntalya
Periyot15/05/1718/05/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Pathologic voice detection
  • big data
  • machine learning
  • voice cloud
  • voice treatment

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