Authors :
Sharath Kumar Shetty; Vijayananda Kumara M; Visakh G Panicker
Volume/Issue :
Volume 7 - 2022, Issue 11 - November
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3Wm52qT
DOI :
https://doi.org/10.5281/zenodo.7547674
Abstract :
This review aims to determine the
applications of ArtificialIntelligence (AI) that are
extensively employed in the field of Orthodontics, to
evaluate its benefits, and to discuss its potential
implications in this speciality. Recentdecades have
witnessed enormous changes in our profession. The
arrival of newand more aesthetic options in orthodontic
treatment, the transition to a fully digitalworkflow, the
emergence of temporary anchorage devices and new
imaging methods all provide both patients and
professionals with a new focus in orthodontic care.A
scoping review of the literature was carried out following
the PRISMA-ScR guidelines. PubMed was searched
until July 2022.Additionalmanual searches were
performed.Forty four articles fulfilled the inclusion
criteria. A total of 30 out of the 44 studies (68.18%) were
published this last decade. The majority of these studies
were from the USA (11), followed by South Korea (9)
and China (7). The number of studies published in nonorthodontic journals (26) was more extensive than in
orthodontic journals (18). Artificial Neural Networks
(ANNs) were found to be the most commonly utilized
AI/ML algorithm (13 studies), followed by Convolutional
Neural Networks (CNNs), Support Vector Machine
(SVM) (9 studies each), and regression (8 studies). The
most commonly studied domains were diagnosis and
treatment planning—either broad-based orspecific (33),
assessment of growth and development(4), and
evaluation of treatment outcomes (2). The different
characteristics and distribution of these studies havebeen
displayed and elucidated upon therein. This scoping
review suggests that there has been an exponential
increase in the number of studies involving various
orthodontic applications of AI and ML. The most
commonly studied domains were diagnosis and
treatment planning, automated anatomic landmark
detection and/or analyses, and growth and development
assessment. In the growth and development research
area, the Cervical Vertebral Maturation stage can be
determined using an Artificial Neural Network model
and obtain the same results as expert human observers.
AI technology can also improve the diagnostic accuracy
for orthodontic treatments.
Keywords :
artificial intelligence, machine learning, orthodontics, review
This review aims to determine the
applications of ArtificialIntelligence (AI) that are
extensively employed in the field of Orthodontics, to
evaluate its benefits, and to discuss its potential
implications in this speciality. Recentdecades have
witnessed enormous changes in our profession. The
arrival of newand more aesthetic options in orthodontic
treatment, the transition to a fully digitalworkflow, the
emergence of temporary anchorage devices and new
imaging methods all provide both patients and
professionals with a new focus in orthodontic care.A
scoping review of the literature was carried out following
the PRISMA-ScR guidelines. PubMed was searched
until July 2022.Additionalmanual searches were
performed.Forty four articles fulfilled the inclusion
criteria. A total of 30 out of the 44 studies (68.18%) were
published this last decade. The majority of these studies
were from the USA (11), followed by South Korea (9)
and China (7). The number of studies published in nonorthodontic journals (26) was more extensive than in
orthodontic journals (18). Artificial Neural Networks
(ANNs) were found to be the most commonly utilized
AI/ML algorithm (13 studies), followed by Convolutional
Neural Networks (CNNs), Support Vector Machine
(SVM) (9 studies each), and regression (8 studies). The
most commonly studied domains were diagnosis and
treatment planning—either broad-based orspecific (33),
assessment of growth and development(4), and
evaluation of treatment outcomes (2). The different
characteristics and distribution of these studies havebeen
displayed and elucidated upon therein. This scoping
review suggests that there has been an exponential
increase in the number of studies involving various
orthodontic applications of AI and ML. The most
commonly studied domains were diagnosis and
treatment planning, automated anatomic landmark
detection and/or analyses, and growth and development
assessment. In the growth and development research
area, the Cervical Vertebral Maturation stage can be
determined using an Artificial Neural Network model
and obtain the same results as expert human observers.
AI technology can also improve the diagnostic accuracy
for orthodontic treatments.
Keywords :
artificial intelligence, machine learning, orthodontics, review
