Open AccessApplication of Machine Learning to Stomatology: A Comprehensive Review
Author(s) -
Mao-Lei Sun,
Yun Liu,
Guomin Liu,
Dan Cui,
Ali Asghar Heidari,
Wen-Yuan Jia,
Xuan Ji,
Huiling Chen,
Yungang Luo
Publication year - 2020
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2020.3028600
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
In recent years, machine learning methods has been widely used in various fields, such as finance, spatial sciences, smart grid, intelligent transportation, renewable energy, agriculture, especially medicine. In the era of big medical data, the advantage of machine learning is that it can predict and diagnose through the analysis of a large number of clinical data, and its performance is very close and competitive to or even better than the performance of clinicians. This article focuses on the application of machine learning techniques in the field of stomatology and detailedly describes application cases involving oral cancer, dental caries, periodontitis, dental pulp diseases, periapical lesions, oral implants, and orthodontics. Finally, the research obstacles and future work are discussed.
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