RESEARCH PAPER
The application of Bayesian networks to estimate the marginal probability of leakage in dental composite reconstructions
1
Wydział Transportu i Informatyki, Wyższa Szkoła Ekonomii i Innowacji, Poland
2
Wydział Lekarsko-Dentystyczny, Uniwersytet Medyczny w Lublinie, Poland
3
Akademia Pożarnicza, Poland
Submission date: 2026-04-16
Acceptance date: 2026-05-05
Online publication date: 2026-05-15
Corresponding author
Agata Niewczas
Wydział Lekarsko-Dentystyczny, Uniwersytet Medyczny w Lublinie, W. Chodźki 6, 20-093, Lublin, Poland
Wydział Lekarsko-Dentystyczny, Uniwersytet Medyczny w Lublinie, W. Chodźki 6, 20-093, Lublin, Poland
KEYWORDS
sieci Bayesaprognozowanie niezawodnościstomatologiczne rekonstrukcje materiałowenieszczelność brzeżnaobserwacje powierzchniowe i podpowierzchniowe
TOPICS
ABSTRACT
This study presents the application of the Bayesian method to estimate the probability of critical marginal leakage in dental restorations. Aim of the study was to evaluate the effectiveness of the Bayesian method in estimating the probability of leakage associated with gap in the subsurface layers of composite restorations, based on observations of their surfaces. The study, involving the construction of a Bayesian network model and probabilistic inference, was based on the results of experimental research. These results were used to verify the a priori and a posteriori probabilities of damage to the tooth-restoration system in three zones of the tooth’s anatomical structure and across four load level intervals; using a Bayesian classifier, the study demonstrated the potential for diagnosing critical subsurface leaks. The results obtained show that surface fissure parameters can support the probabilistic diagnosis of leakage throughout the entire volume of the restorative filling, thereby assisting in clinical decision-making regarding the replacement of damage fillings
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