AIMC Topic: Dental Implants

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Deep learning-based prediction of possibility for immediate implant placement using panoramic radiography.

Scientific reports
In this study, we investigated whether deep learning-based prediction of immediate implant placement is possible. Panoramic radiographs of 201 patients with 874 teeth (Group 1: 440 teeth difficult to place implant immediately after extraction, Group ...

Precise multi-factor immediate implant placement decision models based on machine learning.

Scientific reports
This study aims to explore the effect of implant apex design, osteotomy preparation, intraosseous depth and bone quality on immediate implant placement insertion torque and establish a more sophisticated decision model with multi-factor analysis base...

Optimizing dental implant identification using deep learning leveraging artificial data.

Scientific reports
This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using...

Artificial Intelligence in Detecting and Segmenting Vertical Misfit of Prosthesis in Radiographic Images of Dental Implants: A Cross-Sectional Analysis.

Clinical oral implants research
OBJECTIVE: This study evaluated ResNet-50 and U-Net models for detecting and segmenting vertical misfit in dental implant crowns using periapical radiographic images.

Mental Models of Smart Implant Technology: A Topic Modeling Approach to the Role of Initial Information and Labeling.

Health communication
Public understanding of medical innovations such as smart technology is decisive for its acceptance and implementation. Thus, it is important to understand what visions people develop of a technology based on initial information such as the label. We...

Artificial intelligence for dental implant classification and peri-implant pathology identification in 2D radiographs: A systematic review.

Journal of dentistry
OBJECTIVE: This systematic review aimed to summarize and evaluate the available information regarding the performance of artificial intelligence on dental implant classification and peri-implant pathology identification in 2D radiographs.

Automated segmentation of dental restorations using deep learning: exploring data augmentation techniques.

Oral radiology
OBJECTIVES: Deep learning has revolutionized image analysis for dentistry. Automated segmentation of dental radiographs is of great importance towards digital dentistry. The performance of deep learning models heavily relies on the quality and divers...

DEEP LEARNING-DRIVEN SEGMENTATION OF DENTAL IMPLANTS AND PERI-IMPLANTITIS DETECTION IN ORTHOPANTOMOGRAPHS: A NOVEL DIAGNOSTIC TOOL.

The journal of evidence-based dental practice
INTRODUCTION AND OBJECTIVE: Dental implants are well-established for restoring partial or complete tooth loss, with osseointegration being essential for their long-term success. Peri-implantitis, marked by inflammation and bone loss, compromises impl...