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akaturk Akademik ölçüm

Makale detayı · 2017 · article

Multimedia Respiratory Database (RespiratoryDatabase@TR): Auscultation Sounds and Chest X-rays

ISSN2458-8989
YÖKSİS OpenAlex Açık erişim · diamond
Yıl2017
Atıf41OpenAlex
Atıf57Semantic Scholar · 6 etkili
Yüzdelik%79,5
FWCI1,11,00 = dünya ortalaması
Scopus (SJR)Q3

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıNatural and Engineering Sciences
  • Katalog eşleşmesi (ISSN)Natural and Engineering Sciences
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

Auscultation is a method for diagnosis of especially internal medicine diseases such as cardiac, pulmonary and cardio-pulmonary by listening the internal sounds from the body parts. It is the simplest and the most common physical examination in the assessment processes of the clinical skills. In this study, the lung and heart sounds are recorded synchronously from left and right sides of posterior and anterior chest wall and back using two digital stethoscopes in Antakya State Hospital. The chest X-rays and the pulmonary function test variables and spirometric curves, the St. George respiratory questionnaire (SGRQ-C) are collected as multimedia and clinical functional analysis variables of the patients. The 4 channels of heart sounds are focused on aortic, pulmonary, tricuspid and mitral areas. The 12 channels of lung sounds are focused on upper lung, middle lung, lower lung and costophrenic angle areas of posterior and anterior sides of the chest. The recordings are validated and labelled by two pulmonologists evaluating the collected chest x-ray, PFT and auscultation sounds of the subjects. The database consists of 30 healthy subjects and 45 subjects with pulmonary diseases such as asthma, chronic obstructive pulmonary disease, bronchitis. The novelties of the database are the combination ability between auscultation sound results, chest X-ray and PFT; synchronously assessment capability of the lungs sounds; image processing based computerized analysis of the respiratory using chest X-ray and providing opportunity for improving analysis of both lung sounds and heart sounds on pulmonary and cardiac diseases.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

41atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yerel katalogda bu makaleye atıf yapan 10 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).

  1. 2020 Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary DiseaseAtıf 162 · OpenAlex
  2. 2020 Deep Learning on Computerized Analysis of Chronic Obstructive Pulmonary DiseaseAtıf 162 · OpenAlex
  3. 2018 Deep learning with 3D-second order difference plot on respiratory soundsAtıf 91 · OpenAlex
  4. 2018 Deep learning with 3D-second order difference plot on respiratory soundsAtıf 88 · OpenAlex
  5. 2021 Detection of coronavirus disease (COVID-19) from X-ray images using deep convolutional neural networksAtıf 33 · OpenAlex
  6. 2021 Computer-Aided Diagnosis System for Chronic Obstructive Pulmonary Disease Using Empirical Wavelet Transform on Auscultation SoundsAtıf 23 · OpenAlex
  7. 2018 Hessenberg Elm Autoencoder Kernel For Deep LearningAtıf 21 · OpenAlex
  8. 2018 Superiorities of Deep Extreme Learning Machines against Convolutional Neural NetworksAtıf 21 · OpenAlex
  9. 2020 Effect of Deep Learning Feature Inference Techniques on Respiratory SoundsAtıf 4 · OpenAlex
  10. 2019 The Diagnosis of Asthma using Hilbert-Huang Transform and Deep Learning on Lung SoundsAtıf 2 · OpenAlex

Yazarlar

5
  1. GÖKHAN ALTAN İSKENDERUN TEKNİK ÜNİVERSİTESİ 1
  2. YAKUP KUTLU İSKENDERUN TEKNİK ÜNİVERSİTESİ 2
  3. YUSUF GARBİ 3
  4. ADNAN ÖZHAN PEKMEZCİ 4
  5. SERKAN NURAL 5