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September 16, 2025International Journal Software Engineering and Computer Science (IJSECS)

Development and Evaluation of an Expert System for the Early Diagnosis of Dental Diseases

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Authors

EPEko PurwantoDSDevi Pramita SariFMFarahwahida Mohd

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Overview

This study demonstrates an expert system achieving 92% accuracy in diagnosing dental diseases, highlighting its utility for underserved populations.

Key Points

  • The system achieved a diagnostic accuracy of 92%, showing reliable performance under testing conditions.
  • Usability assessments revealed an impressive 85% satisfaction rate among users engaging with the expert system.
  • Employing Forward Chaining and the Certainty Factor enhances diagnosis by inferring potential conditions from symptoms.
  • Findings indicate the expert system could improve dental disease diagnosis in remote areas, emphasizing the importance of accessible healthcare.

Cite This Study

Purwanto et al. (2025) studied this question.

synapsesocial.com/papers/68d4506b31b076d99fa57715https://doi.org/10.35870/ijsecs.v5i2.4500
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Implementing the Certainty Factor Method in a Dental Disease Expert System2024 · 1 citations
  2. 2Advancing Animal Health: A Web-Based Expert System Utilizing Forward Chaining for Disease Diagnosis2024
  3. 3An expert system for diagnosing and treating heart disease2024
  4. 4Detection of Cardiovascular Disease Using AI2024 · 1 citations
  5. 5Accuracy and Implementation of Dental Clinical Decision Support Systems in Indonesia for Dental Caries and Periodontal Disease2025