A fuzzy mobile decision support system for diagnosing of the angiographic status of heart disease
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Abstract
In estimating the risk of heart disease due to non-deterministic risk factors, often diagnosis of angiographic disease is difficult for physicians. For modeling and application of this uncertain and imprecise modality, decision support systems based on fuzzy logic are appropriate and an effective approach. Smartphone-based applications can facilitate the efficient use of these systems in form of evidence-based medicine. The aim of this applied study was developing and evaluating an application to diagnose angiographic disease conditions and the severity of heart attacks through a smartphone-based clinical decision support system. Android application development environment was utilized after extraction of linguistic rules and definition of membership functions needed for decisions. A smartphone-based application was designed using these guidelines and utilizing fuzzy modeling. Then, the app was evaluated in terms of accuracy using the popular Cleveland dataset. According to the results, 10 fuzzy rules for modeling, seven input variables and one decision variable were extracted. Programming was done in Eclipse. The evaluation results indicate that the accuracy of the program was 94%. Decision support systems within the context of mobile health have become some of the most efficient and influential information technology tools in recent years. They can improve patient-care management, provide easier access to the information needed for healthcare decisions and ultimately reduce healthcare costs while improving its quality.
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