Automatic lung sound analysis accuracy: a validation study

O. Kharevich (Minsk, Belarus), E. Lapteva (Minsk, Belarus), I. Kovalenko (Minsk, Belarus), E. Katibnikova (Minsk, Belarus), A. Pozdnyakova (Minsk, Belarus), A. Laptev (Minsk, Belarus), V. Korovkin (Minsk, Belarus), I. Bezruchko (Minsk, Belarus), G. Novskaya (Minsk, Belarus), I. Lantuchova (Minsk, Belarus), E. Monosova (Minsk, Belarus), M. Zhurovich (Minsk, Belarus), I. Dulub (Minsk, Belarus), O. Adamovich (Minsk, Belarus), V. Hotko (Minsk, Belarus), A. Mathioudakis (Manchester, United Kingdom), H. Binetskaya (Tallin, Estonia), A. Karankevich (Tallin, Estonia), V. Dubinetski (Tallin, Estonia)

Source: Virtual Congress 2021 – Digital health interventions in respiratory medicine
Session: Digital health interventions in respiratory medicine
Session type: E-poster
Number: 3456

Congress or journal article abstractE-poster

Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
O. Kharevich (Minsk, Belarus), E. Lapteva (Minsk, Belarus), I. Kovalenko (Minsk, Belarus), E. Katibnikova (Minsk, Belarus), A. Pozdnyakova (Minsk, Belarus), A. Laptev (Minsk, Belarus), V. Korovkin (Minsk, Belarus), I. Bezruchko (Minsk, Belarus), G. Novskaya (Minsk, Belarus), I. Lantuchova (Minsk, Belarus), E. Monosova (Minsk, Belarus), M. Zhurovich (Minsk, Belarus), I. Dulub (Minsk, Belarus), O. Adamovich (Minsk, Belarus), V. Hotko (Minsk, Belarus), A. Mathioudakis (Manchester, United Kingdom), H. Binetskaya (Tallin, Estonia), A. Karankevich (Tallin, Estonia), V. Dubinetski (Tallin, Estonia). Automatic lung sound analysis accuracy: a validation study. 3456

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.


Related content which might interest you:
Validation of a (semi)-automatic measurement- and control platform for centralized, simultaneous electronic nose (eNose) analyses in multi-centre trials
Source: Annual Congress 2011 - Phenotyping and monitoring of airway diseases
Year: 2011

Calibration of a (semi)-automatic measurement and control platform for centralized, simultaneous electronic nose (eNose) analyses in multi-centre trials
Source: Annual Congress 2012 - Exhaled biomarkers to assess airway inflammation
Year: 2012



Late Breaking Abstract - External validation of exhaled-breath analysis to detect non-small cell lung cancer: a step-wise design to simultaneously develop and validate a prediction model
Source: Virtual Congress 2020 – Screening and imaging in lung cancer
Year: 2020




Reproducibility of 3He-MRI acquisition assessed by a deep learning approach: ventilation defects in the VaPE-Tox pilot study
Source: Virtual Congress 2020 – Imaging-based phenotyping in pulmonary disease
Year: 2020


Comparison of observer variability and accuracy of different criteria for lung scan interpretation
Source: Eur Respir J 2001; 18: Suppl. 33, 226s
Year: 2001

Automated volumetric quantification of lung emphysema: comparative analysis of different software products results.
Source: Virtual Congress 2020 – Investigations of COPD
Year: 2020


Comparative assessment of several automatic CPAP devices' responses: a bench test study
Source: ERJ Open Res 2015
Year: 2015



Application of machine learning algorithms to predict loss of asthma control: A post-hoc analysis of INCONTRO study
Source: Virtual Congress 2020 – Clinical characteristics and diagnostic tools for phenotyping asthma and COPD
Year: 2020


Probability of malignancy based on automatic segmentation and software measurements of nodules in the Danish lung cancer screening trial (DLCST)
Source: Annual Congress 2012 - Screening, diagnosis, staging and treatment strategies for lung cancer
Year: 2012


The use of computer aided lung sound analysis to characterise lung sounds in a healthy population
Source: Annual Congress 2009 - Respiratory physiotherapy assessment
Year: 2009


Assessing the feasibility of GSK’s clinical genetic data re-use for drug target identification and validation: A respiratory case study
Source: International Congress 2017 – Asthma genetics and genomics in patients and populations
Year: 2017

External validation of the French predictive model to estimate PAH survival: A REVEAL analysis
Source: Annual Congress 2012 - Pulmonary circulation: clinical databases and registries
Year: 2012


Early detection of lung disease in firefighters: A sound frequency analysis
Source: International Congress 2015 – Occupational disease: clinical cases and series
Year: 2015


Multicenter study on the variability of the sleep stage scoring algorithm ARTISANA compared to human experts – Part II: validation phase
Source: Eur Respir J 2005; 26: Suppl. 49, 114s
Year: 2005

Vibration response imaging as a new tool for outcome assessment of interventional bronchoscopy: A multi-center validation study
Source: Annual Congress 2010 - Tissue is mostly the issue: diagnostic and therapeutic bronchoscopy
Year: 2010


Performance of a digital signal processing algorithm for the accurate quantification of cough frequency
Source: Eur Respir J, 58 (2) 2004271; 10.1183/13993003.04271-2020
Year: 2021



The concordance of manual (visual) scoring and automatic analysis in sleep staging
Source: Annual Congress 2008 - Diagnostic aspects of sleep apnoea
Year: 2008


The experience of use of the computerized lung sound analysis in the evaluation of nebulaser bronchodilating
Source: Eur Respir J 2007; 30: Suppl. 51, 375s
Year: 2007

Validation of lung nodule detection a year before diagnosis in NLST dataset based on a deep learning system
Source: Virtual Congress 2021 – New clinical and biological developments in lung cancer
Year: 2021