A rule-based decision-making diagnosis system to evaluate arteriovenous shunt stenosis for hemodialysis treatment of patients using fuzzy petri nets.
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.
Wei-Ling
WL
Chen
Chung-Dann
CD
Kan
Chia-Hung
CH
Lin
Tainsong
T
Chen
D000465:Algorithms; D001166:Arteriovenous Shunt, Surgical; D003251:Constriction, Pathologic / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D007676:Kidney Failure, Chronic / Q000628:therapy*; D008875:Middle Aged; D006435:Renal Dialysis; D014463:Ultrasonography