Syntactic pattern recognition of ECG for diagnostic justification

Machine Graphics and Vision Pub Date : 2012-01-14 DOI:10.22630/mgv.2014.23.3.4

P. Flasinski

引用次数: 3

Abstract

A novel hybrid structural-parametric model for ECG diagnostic justification is presented in the paper. In order to distinguish between specific subclasses of heart dysfunction phenomena both grammars and automata are enhanced with a formalism of dynamic programming. It allows one to construct a system, which is feasible for aiding a process of teaching and evaluating medical students' diagnostic reasoning in the area of electrocardiography.

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心电图语法模式识别诊断依据

提出了一种新的用于心电诊断的结构-参数混合模型。为了区分心功能障碍现象的特定子类，语法和自动机都用动态规划的形式来增强。它允许一个人构建一个系统，这是可行的，以帮助教学过程和评估医学生的诊断推理在心电图领域。

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

Machine Graphics and Vision Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

0.40

自引率

0.00%

发文量

期刊介绍： Machine GRAPHICS & VISION (MGV) is a refereed international journal, published quarterly, providing a scientific exchange forum and an authoritative source of information in the field of, in general, pictorial information exchange between computers and their environment, including applications of visual and graphical computer systems. The journal concentrates on theoretical and computational models underlying computer generated, analysed, or otherwise processed imagery, in particular: - image processing - scene analysis, modeling, and understanding - machine vision - pattern matching and pattern recognition - image synthesis, including three-dimensional imaging and solid modeling

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