Detection of dental restorations using no-code artificial intelligence.

Objectives: The purpose of this study was to utilize a no-code computer vision platform to develop, train, and evaluate a model specifically designed for segmenting dental restorations on panoramic radiographs.

Methods: One hundred anonymized panoramic radiographs were selected for this study. Accurate labeling of dental restorations was performed by calibrated dental faculty and students, with subsequent final review by an oral radiologist.

An in-vitro analysis of the accuracy of different guided surgery systems - They are not all the same.

Objectives: Different static computer-assisted implant surgery (sCAIS) systems are available that are based on different design concepts. The objective was to assess seven different systems in a controlled environment.

Materials And Methods: Each n = 20 implants were placed in identical mandible replicas (total n = 140).