Journal ArticleDOI
Classifier for the functional state of the respiratory system via descriptors determined by using multimodal technology.
Sergey Alekseevich Filist,Riad Taha Al-Kasasbeh,O. V. Shatalova,Altyn Amanzholovna Aikeyeva,O. M. Al-Habahbeh,Mahdi Salman Alshamasin,Korenevskiy Nikolay Alekseevich,Mohammad Khrisat,M. B. Myasnyankin,Maksim Urievich Ilyash +9 more
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TLDR
It is shown that the corresponding lines of the wavelet planes are correlated with the respiratory system and, using their Fourier analysis, descriptors can be obtained for training neural network classifiers of the functional state of the respiratory System.Abstract:
Currently, intelligent systems built on a multimodal basis are used to study the functional state of living objects. Its essence lies in the fact that a decision is made through several independent information channels with the subsequent aggregation of these decisions. The method of forming descriptors for classifiers of the functional state of the respiratory system includes the study of the spectral range of the respiratory rhythm and the construction of the wavelet plane of the monitoring electrocardiosignal overlapping this range. Then, variations in the breathing rhythm are determined along the corresponding lines of the wavelet plane. Its analysis makes it possible to select slow waves corresponding to the breathing rhythm and systemic waves of the second order. Analysis of the spectral characteristics of these waves makes it possible to form a space of informative features for classifiers of the functional state of the respiratory system. To construct classifiers of the functional state of the respiratory system, hierarchical classifiers were used. As an example, we took a group of patients with pneumonia with a well-defined diagnosis (radiography, X-ray tomography, laboratory data) and a group of volunteers without pulmonary pathology. The diagnostic sensitivity of the obtained classifier was 76% specificity with a diagnostic specificity of 82%, which is comparable to the results of X-ray studies. It is shown that the corresponding lines of the wavelet planes are correlated with the respiratory system and, using their Fourier analysis, descriptors can be obtained for training neural network classifiers of the functional state of the respiratory system.read more
Citations
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Proceedings ArticleDOI
Local Walsh-Hadamard spectra in video sequence image classifiers
TL;DR: In this article , the Walsh-Hadamard transform was used to form descriptors of weak classifiers for classification of ultrasound images of the pancreas, and a method and software have been developed for classifying video images, which allows the user to create a database of class features, determine the two-dimensional Walsh-hadamard spectrum of segments, train fully connected neural networks, and perform exploratory analysis to study the relevance of spectral coefficients.
Proceedings ArticleDOI
Local Walsh-Hadamard spectra in video sequence image classifiers
Riad Taha Al-Kasasbeh,Tokmakova Rimma Alexandrovna,S. A. Filist,Reutov Dmitry Konstantinovich,Ashraf Adel Shaqadan,Nikolay Aleexevich Korenevskiy,Osama Al-Habahbeh +6 more
TL;DR: In this article , the Walsh-Hadamard transform was used to form descriptors of weak classifiers for classification of ultrasound images of the pancreas, and a method and software have been developed for classifying video images, which allows the user to create a database of class features, determine the two-dimensional Walsh-hadamard spectrum of segments, train fully connected neural networks, and perform exploratory analysis to study the relevance of spectral coefficients.
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Development of Bioimpedance Spectroscopy Technology in Medical Decision Support Systems
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Algorithms for Monitoring the Effectiveness of Therapeutic and Rehabilitation Procedures Based on Clinical Blood Analysis Indicators in the Medical Decision Support System
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