Localized hybrid reasoning system for TB disease diagnosis
Adane Nega · 2015
Hybrid reasoning systems are increasingly used to improve the quality of medical services. Physicians can use the hybrid reasoning systems to diagnose a particular patient's disease. Local languages can be integrated with hybrid reasoning systems to allow end-users communicate with the system in a simpler and easier way. This study presents localized hybrid reasoning systems that uses a combination of rule based reasoning (RBR) and case based reasoning (CBR) techniques using Ethiopian national language to achieve TB disease diagnosis. To develop the localized hybrid reasoning system, knowledge is acquired from documented and non-documented sources. The localized hybrid reasoning system is developed using SWI Prolog version 6.4.1 programming language. The system is tested and evaluated to ensure that whether the performance of the system is accurate and the system is usable by physicians and patients. The localized hybrid reasoning system (LHRS) has an average accuracy of 85.5%.