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基于规则的决策诊断系统,使用模糊 Petri 网评估用于患者血液透析治疗的动静脉分流狭窄。

A rule-based decision-making diagnosis system to evaluate arteriovenous shunt stenosis for hemodialysis treatment of patients using fuzzy petri nets.

出版信息

IEEE J Biomed Health Inform. 2014 Mar;18(2):703-13. doi: 10.1109/JBHI.2013.2279595.

Abstract

This paper proposes a rule-based decision-making diagnosis system to evaluate arteriovenous shunt (AVS) stenosis for long-term hemodialysis treatment of patients using fuzzy petri nets (FPNs). AVS stenoses are often associated with blood sounds, resulting from turbulent flow over the narrowed blood vessel. Phonoangiography provides a noninvasive technique to monitor the sounds of the AVS. Since the power spectra changes in frequency and amplitude with the degree of AVS stenosis, it is difficult to make a human-made decision to judge the degree using a combination of those variances. The Burg autoregressive (AR) method is used to estimate the frequency spectra of a phonoangiographic signal and identify the characteristic frequencies. A rule-based decision-making method, FPNs, is designed as a decision-making system to evaluate the degree of stenosis (DOS) in routine examinations. For 42 long-term follow-up patients, the examination results show the proposed diagnosis system has greater efficiency in evaluating AVS stenosis.

摘要

本文提出了一种基于规则的决策诊断系统,使用模糊 Petri 网(FPN)评估长期血液透析治疗患者的动静脉分流(AVS)狭窄。AVS 狭窄通常与血流声音有关,是由于狭窄血管中的湍流引起的。血管声描记术提供了一种监测 AVS 声音的非侵入性技术。由于功率谱随 AVS 狭窄程度在频率和幅度上发生变化,因此很难通过组合这些变化来做出人工决策来判断狭窄程度。Burg 自回归(AR)方法用于估计血管声描记信号的频谱并识别特征频率。基于规则的决策方法,即模糊 Petri 网(FPN),被设计为决策系统,以评估常规检查中的狭窄程度(DOS)。对于 42 名长期随访患者,检查结果表明,所提出的诊断系统在评估 AVS 狭窄方面具有更高的效率。

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