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Документ Evaluating the Effectiveness of Electrocardiological Study Using Cardiological Decision Support Systems(2020) Filatova, A. E.; Skarga-Bandurova, Inna; Brezhniev, Eugene; Fahs, MohamadThis work is devoted to evaluating the effectiveness of the electrocardiological study process without using and using cardiological decision support systems. To assess the effectiveness, analytical expressions of the probabilistic-time characteristics of the developed structural model of the electrocardiological study process are used. An analysis of the time characteristics of the model is performed when different initial conditions are set for three different types of electrocardiological studies: the study is conducted for the first time, the study is repeated as a result of screening, the study is repeated after treatment. The work shows that the use of cardiological decision support systems based on the developed methods for analyzing biomedical signals with locally concentrated features reduced the average time required for the electrocardiological study of each of the considered types.Документ Method of automatic determination of the heart’s electrical axis in cardiological decision support systems(Одеський національний політехнічний університет, 2021) Filatova, A. E.; Fahs, MohamadThe work is devoted to solving the scientific and practical problem of automating the heart’s electrical axis calculation to im-prove the quality of morphological analysis of biomedical signals with locally concentrated features in cardiological decision support systems, which in turn reduces the likelihood of medical errors. The work shows that existing methods for in the determining the electrical axis of the heart require morphological analysis of an electrocardiogram. The method is based on determining the integral signal in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system. In graphic form in polar coordinates, the integral electrocardiological signal is a figure, predominantly elongated along the axis, the direction’n of which corresponds to the heart’s electrical axis. The position of the heart’s electrical axis is calculated as the angle between the axis of standard lead I and the vector, the end of which is at the center of mass of the locus of the points the farthest away from the reference point. Cluster analysis is used to find the most distant points from the reference point. The proposed method for of calculating the heart’s electrical axis makes it possible not to carry out a preliminary morphological analysis of an electrocardiogram. To implement the method proposed in the article, a program was written in the Matlab language, which is connected as a dynamic link library to the cardiological decision support system “TREDEX telephone” operating as part of the medical diagnostic complex “TREDEX” manu-factured by “Company TREDEX” LLC, Kharkiv. Verification of the results was carried out using a database of electrocardiograms, which were recorded using a transtelephone digital 12-channel electrocardiological complex “Telecard”, which is part of the medical diagnostic complex “TREDEX”, and deciphered by cardiologists of the communal non-profit enterprise of the Kharkiv Regional Council “Center for Emergency Medical aid and disaster medicine”. Comparison of the results of calculating the heart’s electrical axis according to electrocardiograms by a doctor and automatically using the proposed method showed that in the overwhelming majority of cases the decisions made coincide. At the same time, cardiologists make mistakes, and errors are made during automatic calculation using the proposed method. The paper explains the reasons for these errors.Документ Оценка эффективности принятия решений в процессе электрокардиологического исследования(Екологія, 2020) Филатова, Анна Евгеньевна; Фахс, М.Данная работа посвящена оценке эффективности процесса электрокардиологического исследования без использования и с использованием кардиологических систем поддержки принятия решений. Для оценки эффективности используются полученные аналитические выражения вероятностно-временных характеристик разработанной структурной модели процесса электрокардиологического исследования. В работе показано, что использование кардиологических систем поддержки принятия решений, основанных на разработанных методах анализа биомедицинских сигналов с локально сосредоточенными признаками, сократило среднее время, необходимое для электрокардиологического исследования, и увеличило вероятность успешного завершения рассматриваемого процесса.