Employing Fuzzy Cognitive Map for Periodontal Disease Assessment
Periodontal disease is a chronic bacterial infection that affects the gums and bone supporting the teeth. This research work aims to assess the severity level of periodontal disease in dental patients. The presence or absence of sign-symptoms and risk fac
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Employing Fuzzy Cognitive Map for Periodontal Disease Assessment Vijay Kumar Mago, Elpiniki I. Papageorgiou and Anjali Mago
Abstract Periodontal disease is a chronic bacterial infection that affects the gums and bone supporting the teeth. This research work aims to assess the severity level of periodontal disease in dental patients. The presence or absence of sign-symptoms and risk factors make it a complicated diagnostic task. Dentist usually relies on his knowledge, expertise and experiences to design the treatment(s). Therefore, it is found that there is a variation among treatments administered by different dentists. The methodology of Fuzzy Cognitive Maps (FCM) was used to model this problem and then to calculate the severity of the periodontal disease. The relationships between different sign-symptoms have been defined using easily understandable linguistic terms following the construction process of FCM and then converted to numeric values using Mamdani inference method. For convenience, a graphical interface of the system has been designed based on FCM modeling and reasoning.
Electronic supplementary material The online version of this article (doi: 10.1007/978-3642-39739-4_20) contains supplementary material, which is available to authorized users. V. K. Mago (B) Faculty of Administrative Sciences, Fairleigh Dickinson University, Vancouver, BC, Canada e-mail: [email protected] E. I. Papageorgiou Department of Computer Engineering, Technological Educational Institute of Central Greece, 3rd Km Old National Road Lamia-Athens, 35100 Lamia, Greece e-mail: [email protected] A. Mago School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada e-mail: [email protected] E. I. Papageorgiou (ed.), Fuzzy Cognitive Maps for Applied Sciences and Engineering, Intelligent Systems Reference Library 54, DOI: 10.1007/978-3-642-39739-4_20, © Springer-Verlag Berlin Heidelberg 2014
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1 Introduction Medical diagnosis is characterized as a complex process due to vague and imprecise values of signs and symptoms. The impact of a sign or symptom on diagnosis is usually not well defined. Conventional methods have a limited contribution in modelling the diagnostic or decision making systems. So, we design a decision making system based on Fuzzy Cognitive Maps (FCM) technique because of the capabilities of FCMs in handling such complex situations. The proposed system aims to be a front-end decision tool about periodontal disease severity level assessment for dentists. Periodontal diseases refer to the diseases that affect periodontal tissues. Majority of the periodontal diseases are related to plaque-affected inflammatory tissues [15]. The range from uncomplicated gum inflammation to serious damage to the tissues and bone supporting teeth can lead to tooth loss. These diseases fall into two categories: • Gingivitis, the breakdown of gum tissues supporting the tooth. • Periodontitis, usually preceded by gingivitis, involves the breakdown of both, gum tissues a
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