| Abstract: | Objective: Differentiating a fourth heart sound (S4), from a split first heart sound (SP1), or
ejection click (EC), is often difficult particularly for inexperienced clinicians. The objective
of this study was to develop and evaluate a computer-assisted classification tool to aid
in this difficult differentiation problem, and in general for heart sound differentiation and
diagnosis.
Design: Developmental study.
Methods: Emphasis was given to the selection of appropriate features that are adequately
independent from the heart sound signal acquisition method. Relevance analysis was initially
performed to identify the features of the heart sound most relevant to aiding diagnosis of
S4, SP1 and EC. To detect and differentiate S4, SP1 and EC, a detection decision tree
(DeDT) and a differentiation decision tree (DiDT) were used independently and also together
in a multiple decision tree architecture. The DeDT provides three suggestions for each heart
sound pattern, whereas the DiDT provides one. The MuDT analyses the suggestions of both
decision trees to provide one final suggestion for each sound pattern.
Results: Relevance analysis on the different heart sound features demonstrated that the
most relevant features for aiding diagnosis of S4, SP1 and EC are the frequency features
and the morphological features that describe S1. The DeDT architecture demonstrated an
average classification accuracy of 80.56%, sensitivity of 70.93%, and specificity of 83.42%,
but provided more than one suggestion for many cases. The DiDT architecture demonstrated
an average classification accuracy of 66.46%, a sensitivity of 66.15% and a specificity
of 82.15%, and only provided one suggestion for each case. The MuDT architecture
slightly improved performance compared to the DiDT architecture. Average classification
accuracy was improved by 2.79%, classification sensitivity by 2.73% and classification
specificity by 1.26%
Conclusions: The present work has demonstrated that decision tree algorithms can be
successfully used as the basis for a decision support system to assist inexperienced clinicians
in heart sound diagnosis. Further work is currently in progress to improve the accuracy,
specificity and sensitivity of the system. |
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