Volume 1, Issue 1 (spring - summer 2014)
DSME 2014, 1(1): 37-44 |
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Khoramian Tusi S, Zeynali B. Investigation of a Decision Making System for Dental Caries Treatment in Children. DSME 2014; 1 (1) :37-44
URL: http://dsme.hums.ac.ir/article-1-43-en.html
URL: http://dsme.hums.ac.ir/article-1-43-en.html
Abstract: (5247 Views)
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.
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.
Type of Study: Orginal |
Subject:
General
Received: 2014/10/22 | Accepted: 2014/10/22 | Published: 2014/10/22
Received: 2014/10/22 | Accepted: 2014/10/22 | Published: 2014/10/22
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