Experiment and Evaluation of Acute Rheumatic Fever Diagnosis Application

Abstract

This paper describes an Acute Rheumatic Fever (ARF) Diagnosis Application that is designed and developed based on the proposed Hybrid Approach. It is an integrated framework in terms of a combination of Knowledge-based System, Temporal Theory and Fuzzy Logic. The developed ARF Diagnosis Application was experimentally tested and evaluated by the experts and users of Nepal Heart Foundation (NHF) NHF by means of using NHF's data sets consisting of 676 real patients' records. The ARF Diagnosis Application was found to match 99 percentage of the cases derived from NHF's datasets. The overall ARF diagnostics performance and accuracy was 99.36 percentage.