Zobrazeno 1 - 10
of 809
pro vyhledávání: '"Lung sounds"'
Publikováno v:
Medičnì Perspektivi, Vol 29, Iss 3, Pp 96-107 (2024)
The main purpose of this work was to investigate the possibility of detecting respiratory diseases in audio recordings of lung auscultation using modern deep learning tools, as well as to explore the possibility of using data augmentation by generati
Externí odkaz:
https://doaj.org/article/0fc63349b4e04fb68330339a6361f679
Autor:
Giacomo Sgalla, Jacopo Simonetti, Arianna Di Bartolomeo, Tonia Magrì, Bruno Iovene, Giuliana Pasciuto, Ruben Dell’Ariccia, Francesco Varone, Alessia Comes, Paolo Maria Leone, Venere Piluso, Alessandro Perrotta, Giuseppe Cicchetti, Diana Verdirosi, Luca Richeldi
Publikováno v:
Respiratory Research, Vol 25, Iss 1, Pp 1-11 (2024)
Abstract Background Although crackles on chest auscultation represent a fundamental component of the diagnostic suspect for fibrotic interstitial lung disease (ILD), their reliability has not been properly studied. We assessed the agreement among res
Externí odkaz:
https://doaj.org/article/47593c4975e946a8bea823fc79056a79
Autor:
Evangelos Kaimakamis, Serafeim Kotoulas, Myrto Tzimou, Christos Karachristos, Chrysavgi Giannaki, Vassileios Kilintzis, Leandros Stefanopoulos, Evangelos Chatzis, Nikolaos Beredimas, Bruno Rocha, Diogo Pessoa, Rui Pedro Paiva, Nicos Maglaveras, Militsa Bitzani
Publikováno v:
Pneumonia, Vol 16, Iss 1, Pp 1-14 (2024)
Abstract Background The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for determining the severity of lung damage. Lung auscultation coul
Externí odkaz:
https://doaj.org/article/84c7d736dd0841fcaad8f7ada8e7ccda
Autor:
Zhaoping Wang, Zhiqiang Sun
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2024, Iss 1, Pp 1-21 (2024)
Abstract It is desired to apply deep learning models (DLMs) to assist physicians in distinguishing abnormal/normal lung sounds as quickly as possible. The performance of DLMs depends on feature-related and model-related parameters heavily. In this pa
Externí odkaz:
https://doaj.org/article/b17dda9006634f548ca59726c31af4ed
Autor:
Xiaoran Xu, Ravi Sankar
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 10, p 127 (2024)
This review explores the latest advances in artificial intelligence (AI) and machine learning (ML) for the identification and classification of lung sounds. The article provides a historical overview from the invention of the electronic stethoscope t
Externí odkaz:
https://doaj.org/article/a105eb8b280848558281cdcbd6a1bf30
Publikováno v:
Heliyon, Vol 10, Iss 4, Pp e26218- (2024)
The use of computer-based automated approaches and improvements in lung sound recording techniques have made lung sound-based diagnostics even better and devoid of subjectivity errors. Using a computer to evaluate lung sound features more thoroughly
Externí odkaz:
https://doaj.org/article/e4c6a2f2c7e843bfb415f57525736a22
Publikováno v:
Medical Devices: Evidence and Research, Vol Volume 15, Pp 89-102 (2022)
Biruk Abera Tessema,1,2 Hundessa Daba Nemomssa,1 Gizeaddis Lamesgin Simegn1 1School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia; 2School of Medicine, Haramaya University College of Health and Medical Sc
Externí odkaz:
https://doaj.org/article/09acfa7334094a47bd314f05944ae12b
Autor:
Juan P. Garcia-Mendez, Amos Lal, Svetlana Herasevich, Aysun Tekin, Yuliya Pinevich, Kirill Lipatov, Hsin-Yi Wang, Shahraz Qamar, Ivan N. Ayala, Ivan Khapov, Danielle J. Gerberi, Daniel Diedrich, Brian W. Pickering, Vitaly Herasevich
Publikováno v:
Bioengineering, Vol 10, Iss 10, p 1155 (2023)
Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models req
Externí odkaz:
https://doaj.org/article/b5748db8c3d64c80820866bf8ab05586
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Akademický článek
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