AIMC Topic: Computer-Aided Design
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Application of 3D neural networks and explainable AI to classify ICDAS detection system on mandibular molars.
The Journal of prosthetic dentistry
Oct 22, 2024
STATEMENT OF PROBLEM: Considerable variations exist in cavity preparation methods and approaches. Whether the extent and depth of cavity preparation because of the extent of caries affects the overall accuracy of training deep learning models remains...
Development and validation of a robotic system for milling individualized jawbone cavities in oral and maxillofacial surgery.
Journal of dentistry
Sep 30, 2024
OBJECTIVES: This study aimed to develop and validate a robotic system capable of performing accurate and minimally invasive jawbone milling procedures in oral and maxillofacial surgery.
Can deep learning-designed anterior tooth-borne crown fulfill morphologic, aesthetic, and functional criteria in clinical practice?
Journal of dentistry
Sep 24, 2024
OBJECTIVES: This study aimed to compare the design outcomes of anterior crowns generated using deep learning (DL)-based software with those fabricated by a technician using conventional dental computer-assisted design (CAD) software without DL suppor...
Introducing a novel approach to dental color reproduction using AI technology.
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Aug 18, 2024
OBJECTIVE: This article aims to describe a systematic method for tooth color reproduction with ceramics restorations employing artificial intelligence (AI) software named Matisse. It provides a comprehensive analysis of the entire process, beginning ...
Improving accuracy and efficiency of the machined PEEK denture based on NSGA-II integrated GABP neural network.
Dental materials : official publication of the Academy of Dental Materials
Aug 10, 2024
OBJECTIVES: The polymer polyetheretherketone (PEEK) is gradually being used in dental restorations because of its excellent mechanical properties, chemical resistance, fatigue resistance, thermal stability, radiation translucency and good biocompatib...
Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study.
International dental journal
Jul 28, 2024
INTRODUCTION AND AIMS: Artificial intelligence (AI) has been adopted in the field of dental restoration. This study aimed to evaluate the time efficiency and morphological accuracy of crowns designed by two AI-powered software programs in comparison ...
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...
Deep learning and explainable artificial intelligence for investigating dental professionals' satisfaction with CAD software performance.
Journal of prosthodontics : official journal of the American College of Prosthodontists
Jul 15, 2024
PURPOSE: This study aimed to examine the satisfaction of dental professionals, including dental students, dentists, and dental technicians, with computer-aided design (CAD) software performance using deep learning (DL) and explainable artificial inte...
Finding Relevant Retrosynthetic Disconnections for Stereocontrolled Reactions.
Journal of chemical information and modeling
Jul 12, 2024
Machine learning-driven computer-aided synthesis planning (CASP) tools have become important tools for idea generation in the design of complex molecule synthesis but do not adequately address the stereochemical features of the target compounds. A no...
Deep learning-designed implant-supported posterior crowns: Assessing time efficiency, tooth morphology, emergence profile, occlusion, and proximal contacts.
Journal of dentistry
Jun 19, 2024
OBJECTIVES: To compare implant supported crowns (ISCs) designed using deep learning (DL) software with those designed by a technician using conventional computer-aided design software.
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