The Possibilities of Diagnosis and Prediction of Cardiac Disorders Based on the Results of Mathematical Modeling of the Myocardium and Regulation of Action of the Heart
IF 0.7
Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
引用次数: 0
Abstract
Theoretical approaches to solving problems of diagnosing and predicting cardiac dysfunctions within the framework of modern mathematical physics of the heart (cardiophysics) are presented. The possibilities for diagnostic purposes of using recognition of patterns of behavior of autowave vortices that arise in the heart during dangerous disturbances in its functioning are considered. The prospects for the development of new methods for diagnosing patterns of the basic heart rhythm in the development of already recognized methods for analyzing heart rate variability are discussed.
根据心肌数学建模和心脏作用调节的结果诊断和预测心脏疾病的可能性
摘要 介绍了在现代心脏数学物理学（心脏物理学）框架内解决诊断和预测心脏功能障碍问题的理论方法。考虑了利用识别心脏功能出现危险干扰时产生的自波涡流的行为模式来进行诊断的可能性。讨论了在发展已被认可的心率变异性分析方法的过程中，开发诊断基本心律模式的新方法的前景。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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来源期刊
PATTERN RECOGNITION AND IMAGE ANALYSIS
Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.80
自引率
20.00%
发文量
80
期刊介绍：
The purpose of the journal is to publish high-quality peer-reviewed scientific and technical materials that present the results of fundamental and applied scientific research in the field of image processing, recognition, analysis and understanding, pattern recognition, artificial intelligence, and related fields of theoretical and applied computer science and applied mathematics. The policy of the journal provides for the rapid publication of original scientific articles, analytical reviews, articles of the world''s leading scientists and specialists on the subject of the journal solicited by the editorial board, special thematic issues, proceedings of the world''s leading scientific conferences and seminars, as well as short reports containing new results of fundamental and applied research in the field of mathematical theory and methodology of image analysis, mathematical theory and methodology of image recognition, and mathematical foundations and methodology of artificial intelligence. The journal also publishes articles on the use of the apparatus and methods of the mathematical theory of image analysis and the mathematical theory of image recognition for the development of new information technologies and their supporting software and algorithmic complexes and systems for solving complex and particularly important applied problems. The main scientific areas are the mathematical theory of image analysis and the mathematical theory of pattern recognition. The journal also embraces the problems of analyzing and evaluating poorly formalized, poorly structured, incomplete, contradictory and noisy information, including artificial intelligence, bioinformatics, medical informatics, data mining, big data analysis, machine vision, data representation and modeling, data and knowledge extraction from images, machine learning, forecasting, machine graphics, databases, knowledge bases, medical and technical diagnostics, neural networks, specialized software, specialized computational architectures for information analysis and evaluation, linguistic, psychological, psychophysical, and physiological aspects of image analysis and pattern recognition, applied problems, and related problems. Articles can be submitted either in English or Russian. The English language is preferable. Pattern Recognition and Image Analysis is a hybrid journal that publishes mostly subscription articles that are free of charge for the authors, but also accepts Open Access articles with article processing charges. The journal is one of the top 10 global periodicals on image analysis and pattern recognition and is the only publication on this topic in the Russian Federation, Central and Eastern Europe.
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