A Framework for Knowledge Capture in African Traditional Treatment of Malaria

Abstract

This study developed, implemented and evaluated a framework for the means of knowledge capture in African traditional medicine (ATM) practice. This was with a view to enhancing the preservation of knowledge and hence the continual exploitation of African traditional healing techniques in malaria therapy. The methodology adopted involved knowledge elicitation by means of an interview scheme administered on a number of African traditional medicine practitioners (ATMPs) in Ile-Ife and its environs. The data taken from the practitioners were analyzed using the general architecture for text engineering (GATE) software. The resulting information was structured and the knowledge based system (KBS) was implemented using Javascript and PHP programming language. Sample cases of malaria were posted to the KBS for diagnosis and treatment of malaria disease. Also, fifteen ATMPs were required to provide diagnosis and therapies for the same cases of malaria in groups of five. The output from the KBS and ATMPs were then tested for agreement using Fleiss’ Kappa qualitative analysis. The diagnosis and therapy agreement between the groups of ATMPs and the KBS gave an average kappa-measure of 0.854 which indicates an almost perfect agreement between the KBS and the ATMPs. Therefore, the framework can be said to be complete for knowledge capture of malaria. In conclusion, knowledge in ATM practice could be structured, formalized and implemented as found in this work. This could be useful for capturing, storing and preserving knowledge in the domain of African traditional medicine practice.

Keywords: African Traditional Medicine, General Architecture For Text Engineering, Knowledge Based System