An Artificial Intelligence Solution for Automated Dental Inspection and Charting.

ABSTRACT:

Background

Visual inspection and documentation (charting) of findings are critical components in dental practice. However, manual charting is tedious, time consuming, and prone to errors. Attempts to automate charting using AI have focused on computer vision of radiographs, which does not replace visual inspection and has limitations in community screening settings. We aim to develop a deep-learning-based real-time charting using intra-oral videos. This study encompasses tooth identification, the initial phase of our development process.

Methods

100 intra-oral videos were recorded, annotated using CVAT software, and split into training and testing datasets (80:20 ratio) to develop an object detection YOLOv7x model on a Convolutional Neural Network (CNN). The model was evalua

SUBMITTER: Moufti MA 

PROVIDER: S-EPMC12206106 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature