Open AccessNeural network classifiers with descriptors obtained on the basis of analysis of the system rhythms in intellectual prediction systems for non-hospital pneumonia
Author(s) -
Maksim Borisovich Myasnyankin,
А. А. Кузьмин,
С. А. Филист
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1801/1/012046
Subject(s) - rhythm , synchronicity , classifier (uml) , community acquired pneumonia , pneumonia , artificial intelligence , computer science , machine learning , pattern recognition (psychology) , medicine , psychology , psychoanalysis
The description of the synthesis of the risk classifier of non-hospital (community-acquired) pneumonia based on predictors is presented in the article. Predictors are compiled by analyzing the synchronicity of the systemic rhythms of the cardiovascular system and the respiratory system. Spectr of cardiac signals and wavelet coefficients of cardiac signals are used as sources of systemic rhythms. An algorithm for classifying the risk of community-acquired pneumonia in terms of synchronicity of system rhythms is proposed in the article.