Multilevel risk management based fuzzy model for the Minnesota Code

The Minnesota Code is the evaluation method of reference ECG signals. The experimental studies compare the effectiveness of the computer based Minnesota Code applications to human usage of the code system, and the results showed that computers are as effective in the evaluation of ECG signal with the Minnesota Code as humans are with visual analysis. In this paper the authors present a fuzzy-based approach to bypass known imperfections and imprecision of the existing Minnesota Code rules with the use of risk management. The fuzzy environment provides more information and this fact is used in the presented solution. The presented algorithm determines the risk of decision tree exclusions and assesses the uncertainty factor with the strict Minnesota rule.