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Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Kamsu-Foguem, Bernard and Diallo, Gayo and Foguem, Clovis Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine. (2013) Engineering Applications of Artificial Intelligence, 26 (4). 1348-1365. ISSN 0952-1976

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Official URL: http://dx.doi.org/10.1016/j.engappai.2012.12.004

Abstract

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring).

Item Type:Article
Additional Information:Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com The original PDF of the article can be found at Engineering Applications of Artificial Intelligence website : http://dx.doi.org/10.1016/j.engappai.2012.12.004
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Institut National de la Recherche Agronomique - INRA (FRANCE)
Other partners > Université de Bourgogne - UB (FRANCE)
Other partners > Université de Bordeaux 2 - Victor Segalen (FRANCE)
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Deposited By: Bernard KAMSU FOGUEM
Deposited On:20 Feb 2013 10:37

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