Using of the machine learning methods to identify bronchopulmonary system diseases with the use of lung sounds
Journal Title: Вісник НТУУ КПІ. Серія Радіотехніка, Радіоапаратобудування - Year 2018, Vol 0, Issue 73
Abstract
This study reviews the main approaches to the analyzing of modern methods of digital processing of lung sounds. It is shown that each of the existing methods gives a definite result in solving a particular problem. However, none of the methods that were reviewed, can’t be called universal and completely convenient for using in the real conditions of the hospital. Certain numerical parameters can be obtained, as a result of the work of each method. In this study it is showed that machine learning can serve as a unifying mechanism for the considered methods. A set of different parameters can be the input arguments of the classifier, which will be properly trained. As a result, the primary opinion in a convenient and accessible form can be presented to the doctor.
Authors and Affiliations
M. Chekhovych, A. Poreva, V. Timofeyev, P. Henaff
Keywords
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- EP ID EP308245
- DOI 10.20535/RADAP.2018.73.55-62
- Views 56
- Downloads 0
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