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Dental Materials

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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
AIM: This study was aimed to investigate the hemocompatibility of zirconia and titanium implant materials after surface treatment with sandblasting and acid etching (SLA).

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

Computational and mathematical methods in medicine
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...

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
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 ...

Fiber Jamming Transition as a Stiffening Mechanism for Soft Robotics.

Soft robotics
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...

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

Computer methods in biomechanics and biomedical engineering
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...

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

Journal of endodontics
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 ...

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

PeerJ
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...

Dental Composite Performance Prediction Using Artificial Intelligence.

Journal of dental research
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...