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Oral Health Diagnosis by Using Combination of Evidence in Dezert-Smarandache Theory

  • Fadhillah, Muhammad Kamil (Division of Computer Science and Engineering, Sun Moon University) ;
  • Listio, Syntia (Division of Computer Science and Engineering, Sun Moon University) ;
  • Choi, Yong Keum (Department of Dental Hygiene, Sun Moon University) ;
  • Lee, Hyun (Division of Computer Science and Engineering, Sun Moon University)
  • Received : 2018.11.02
  • Accepted : 2018.11.20
  • Published : 2018.12.31

Abstract

Based on World Health Organization (WHO) children and adults have a problem with their oral health, such as Dental cavities and periodontal disease. It is not easy to obtain the high convince level of result of the dental and periodontal diseases. Because each of them have different degrees of uncertainty and there have several discounting factors (error rates) in different of survey. To solve this problem we propose the Dezert-Smarandache Theory (DSmT) for efficient combination of uncertain, imprecise and highly conflicting sources of information. Moreover, we apply the SEFP as a context reasoning. Finally, we make the simulation by using 12 surveys and compare Propotional Conflict Redistribution 5 (PCR5) and Dempster-Shafer Theory (DST) to show the belief or probability for the low, a heavy, high and ultra-high risk situation.

Keywords

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Figure 1. Static evidential network based on state-space context modeling.

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Figure 2. Example of User’s Four Possible Reasoning Based on the SEN

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Figure 3. Graphic of the example with maximum Weighting Factors

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Figure 4. Graphic of the example with condition 1

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Figure 5. Graphic of the example with condition 4

Table 1. Weighting factors of dental disease with several condition

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Table 2. Examples of the degrees of the belief or probability for an Uhr situation based on the numbers of activated survey with maximum of weighting factors

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Table 3. Examples of the degrees of the belief or probability for an Uhr situation based on the numbers of activated survey with condition 1

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Table 4. Examples of the degrees of the belief or probability for an Uhr situation based on the numbers of activated survey with condition 1

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References

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