ISSN: 2182-2069 (printed) / ISSN: 2182-2077 (online)
A Belief Rule Based Expert System to Assess Hypertension under Uncertainty
Hypertension (HPT) plays an important role, especially for stroke and heart diseases. Therefore, the accurate assessment of hypertension is becoming a challenge. However, the presence of uncertainties, associated with the signs and symptoms of HPT are becoming crucial to conduct the precise assessment. This article presents a web-based expert system (web BRBES) by employing belief rule based (BRB) methodology to assess HPT, allowing the generation of reliable results. In order to check the reliability of the system, a comparison has been performed among various approaches such as decision tree, random forest, artificial neural networks, fuzzy rule based expert system and experts’ opinion. Different performance metrics such as confusion matrix, accuracy, root mean square error, area under curve have been used to contrast the reliability of the approaches. The BRBES produces a more reliable result than from the other approaches. Moreover, the user friendliness of the web BRBES found high as obtained by using the PACT (People, Activities, Contexts, Technologies) approach over 200 people.