AIMC Topic: Dental Materials

Clear Filters Showing 1 to 10 of 10 articles

Dental Composite Performance Prediction Using Artificial Intelligence.

Journal of dental research Feb 14, 2025
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, t...
Composite Resins Dental Materials Flexural Strength Support Vector Machine Decision Trees Humans Artificial Intelligence Machine Learning
View on PubMed DOI

Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review.

PeerJ Jul 19, 2024
Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize...
Humans Dental Materials Artificial Intelligence Dental Prosthesis Design Computer-Aided Design Dental Restoration, Permanent
View on PubMed DOI

Uncertainty-based Active Learning by Bayesian U-Net for Multi-label Cone-beam CT Segmentation.

Journal of endodontics Nov 17, 2023
INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and ...
Cone-Beam Computed Tomography Image Processing, Computer-Assisted Bayes Theorem Artificial Intelligence Algorithms Dental Materials Uncertainty
View on PubMed DOI

Prediction of abrasive wears behavior of dental composites using an artificial neural network.

Computer methods in biomechanics and biomedical engineering Jun 8, 2022
Resin composites are widely used as dental restorative materials since dental parts are subjected to prolonged wear and ultimately need to be replaced. The objective of this study is to analyze the potential of the feed-forward back propagation artif...
Composite Resins Materials Testing Surface Properties Neural Networks, Computer Bayes Theorem Dental Materials
View on PubMed DOI

Fiber Jamming Transition as a Stiffening Mechanism for Soft Robotics.

Soft robotics Apr 6, 2020
Robots made of soft materials are demonstrating to be well suited in applications where dexterity and intrinsic safety are necessary. However, one of the most challenging goals of soft robotics remains the ability to change the stiffness of body part...
Robotics Equipment Design Dietary Fiber Dental Materials
View on PubMed DOI

An In Vitro Study to Evaluate and Compare the Hemocompatibility of Titanium and Zirconia Implant Materials after Sandblasted and Acid-etched Surface Treatment.

The journal of contemporary dental practice Dec 1, 2018
AIM: This study was aimed to investigate the hemocompatibility of zirconia and titanium implant materials after surface treatment with sandblasting and acid etching (SLA).
Materials Testing Acid Etching, Dental Dental Prosthesis Design In Vitro Techniques Biocompatible Materials Dental Etching Titanium Zirconium Dental Materials
View on PubMed

Use of Artificial Neural Network in Determination of Shade, Light Curing Unit, and Composite Parameters' Effect on Bottom/Top Vickers Hardness Ratio of Composites.

BioMed research international Nov 12, 2018
OBJECTIVE: To assess the influence of light emitting diode (LED) and quartz tungsten halogen (QTH) light curing unit (LCU) on the bottom/top (B/T) Vickers Hardness Number (VHN) ratio of different composites with different shades and determination of ...
Hardness Curing Lights, Dental Materials Testing Analysis of Variance Dental Materials Neural Networks, Computer Composite Resins
View on PubMed DOI

Complete rehabilitation of compromised full dentitions with adhesively bonded all-ceramic single-tooth restorations: Long-term outcome in patients with and without amelogenesis imperfecta.

Journal of dentistry Dec 21, 2017
OBJECTIVES: This clinical follow-up evaluated the long-term outcome of full-mouth rehabilitations with adhesively bonded all-ceramic restorations in patients suffering from amelogenesis imperfecta (AI) or affected by extensive tooth wear including a ...
Dental Restoration Failure Dental Veneers Dentition Survival Rate Incisor Humans Male Periodontal Index Tooth Fractures Female Middle Aged Dental Cements Dental Materials Time Factors Young Adult Dental Marginal Adaptation Amelogenesis Imperfecta Treatment Outcome Tooth Wear Ceramics Adult Bruxism Dental Porcelain Oral Health Dental Bonding
View on PubMed DOI

The prediction in computer color matching of dentistry based on GA+BP neural network.

Computational and mathematical methods in medicine Mar 22, 2015
Although the use of computer color matching can reduce the influence of subjective factors by technicians, matching the color of a natural tooth with a ceramic restoration is still one of the most challenging topics in esthetic prosthodontics. Back p...
Reproducibility of Results Pattern Recognition, Automated Neural Networks, Computer Dental Materials Prosthodontics Humans Software Dentistry Algorithms Prosthesis Coloring
View on PubMed DOI

A machine learning model exploring creep performance of dental composites.

Dental materials : official publication of the Academy of Dental Materials Jul 1, 2025
OBJECTIVES: Viscoelastic creep behaviour of RBCs determines their dimensional stability and thus contributes to their clinical performance. However, due to complex material compositional variations and differing testing protocols, comparing and analy...
Elasticity Viscosity Dental Materials Machine Learning Composite Resins Materials Testing
View on PubMed DOI
Popular Topics
Recent Journals