Dental Composite Performance Prediction Using Artificial Intelligence.

ABSTRACT: There is a need to increase the performance and longevity of dental composites and accelerate the translation of novel composites to the market. This study explores the use of artificial intelligence (AI), specifically machine learning (ML) models, to predict the performance outcomes (POs) of dental composites from their composite attributes. A comprehensive dataset was carefully curated and refined from 200+ publications. Nine ML models were trained to predict discrete POs, and their performance was evaluated. Five models were used for regression analysis of continuous POs. Different ML models performed better on different POs. The k-nearest neighbors (KNN) model excelled in predicting flexural modulus (FlexMod), Decision Tree model in flexural strength (FlexStr) and volumetric shrinkage

SUBMITTER: Paniagua K 

PROVIDER: S-EPMC12000627 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature