FLAPECAN: a knowledge based system in electrocardiogram diagnosis

FLAPECAN is a knowledge-based system designed to aid in the interpretation of electrocardiograms (ECGs). Diagnoses are based upon simple features of the ECG being analyzed. The system may be used to aid in generating diagnoses either by a human user or by an automated analysis system where feature recognition is provided. The system was implemented with fuzzy-logic based inference in FLX, a knowledge representation system. The use of FLX, which provides object- and rule-based paradigms, yields improved organization, a more explicit representation of the ECG domain knowledge, and a graphical development and user environment. Repeated application of the system to known cases provided results for calibration of fuzzy knowledge. As a whole, FLAPECAN shows good initial results, suggesting that such an application of fuzzy reasoning has a promising future.<
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