Machine learning in dental, oral and craniofacial imaging: a review of recent progress
Author(s) -
Ruiyang Ren,
Haozhe Luo,
Chongying Su,
Yang Yao,
Wen Liao
Publication year - 2021
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.11451
Subject(s) - medical imaging , popularity , computer science , artificial intelligence , field (mathematics) , craniofacial , convolutional neural network , data science , medical physics , medicine , psychology , social psychology , mathematics , psychiatry , pure mathematics
Artificial intelligence has been emerging as an increasingly important aspect of our daily lives and is widely applied in medical science. One major application of artificial intelligence in medical science is medical imaging. As a major component of artificial intelligence, many machine learning models are applied in medical diagnosis and treatment with the advancement of technology and medical imaging facilities. The popularity of convolutional neural network in dental, oral and craniofacial imaging is heightening, as it has been continually applied to a broader spectrum of scientific studies. Our manuscript reviews the fundamental principles and rationales behind machine learning, and summarizes its research progress and its recent applications specifically in dental, oral and craniofacial imaging. It also reviews the problems that remain to be resolved and evaluates the prospect of the future development of this field of scientific study.
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