Investigation of a Decision Making System for Dental Caries Treatment in Children

• Main Authors: Somayeh Khoramian Tusi, Behnam Zeynali
• Format: Article
• Language: fas
• Published: Hormozgan University of Medical Sciences 2014-04-01
• Series: Development Strategies in Medical Education
• Subjects: Bayesian Network; Decision making system; Dentist; Uncertainty
• Online Access: http://dsme.hums.ac.ir/browse.php?a_code=A-10-2-5&slc_lang=en&sid=1

 Introduction: Dentists have to choose a precise treatment plan based on the prevailing sign symptoms gathered from patients. However; in most of cases, the symptoms are complicate which makes the lack of confidence for the dentist to find an accurate treatment plan. This study introduces a new diagnosis system that helps the dentists and students to choose an accurate course of treatment for dental caries. This diagnostic system is based on Bayesian Network (BN) analysis. Methods: In this system, patient’s symptoms were as input variables and treatments were as output variables. A Bayesian Network is designed for 13 different sign-symptoms and 5 related treatments. K-means clustering algorithm is used to determine the relationships between variables, including symptoms and treatment. Results: The system evaluated by using actual scenario to determine the accuracy and showed reliable outcome. Conclusion: This system can be used in dental schools to teach students.