Dublin Core
Title
Artificial Intelligence in Oral Health
Subject
Oral Health
Description
Artificial intelligence (AI), including deep learning and machine learning, is undergoing rapid
development and has garnered substantial public attention in recent years. In particular, AI is
positioned to become one of the most transformative technologies for medical applications and
demonstrates great potential and useful properties for improving the analysis of various medical
imaging datasets such as plain radiographs or three-dimensional imaging modalities. Several
AI-based deep learning architectures have already been approved by the FDA and are being applied
in clinical practice. In the dental field, the usefulness of AI has been assessed for the detection,
classification, and segmentation of anatomical variables for orthodontic landmarks, dental caries,
periodontal disease, and osteoporosis; however, these applications are still in very preliminary stages
development and has garnered substantial public attention in recent years. In particular, AI is
positioned to become one of the most transformative technologies for medical applications and
demonstrates great potential and useful properties for improving the analysis of various medical
imaging datasets such as plain radiographs or three-dimensional imaging modalities. Several
AI-based deep learning architectures have already been approved by the FDA and are being applied
in clinical practice. In the dental field, the usefulness of AI has been assessed for the detection,
classification, and segmentation of anatomical variables for orthodontic landmarks, dental caries,
periodontal disease, and osteoporosis; however, these applications are still in very preliminary stages
Creator
Jae-Hong Lee (Ed.)
Source
https://www.mdpi.com/books/book/6002-artificial-intelligence-in-oral-health
Publisher
MDPI - Multidisciplinary Digital Publishing Institute
Date
August 2022
Contributor
Dwi Prihastuti
Rights
https://creativecommons.org/licenses/by/4.0/
Format
pdf
Language
English
Type
Textbooks
Identifier
ISBN 978-3-0365-5143-2 (PDF)