TITLE:
Expert System for the Diagnosis and Prognosis of Common Dental Diseases Using Bayes Network
AUTHORS:
Grace Tam-Nurseman, Philip Achimugu, Oluwatolani Achimugu, Hilary Kelechi Anabi, Sseggujja Husssein
KEYWORDS:
Expert System, Dental Diagnosis, Dental Diseases and Human Expert
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.14 No.11,
November
30,
2021
ABSTRACT: Expert systems are being utilized increasingly in medical fields for the purposes of assisting diagnosis and treatment planning. Existing systems used few symptoms for dental diagnosis. In Dentistry, few symptoms are not enough for diagnosis. In this research, a conditional probability model (Bayes rule) was developed with increased number of symptoms associated with a disease for diagnosis. A test set of recurrent cases was then used to test the diagnostic capacity of the system. The generated diagnosis matched that of the human experts. The system was also tested for its capacity to handle uncommon dental diseases and the system portrayed useful potential.