BR-2-1
www.stomaeduj.com
Florin-Eugen
Constantinescu
Machine Learning in Dentistry
DMD, PhD Student
Holistic Dental & Medical Institute
of Bucharest - ROPOSTURO
Editors: Ching-Chang Ko, Dinggang Shen,
Bucharest, Romania
e-mail: dr.florin.constantinescu@gmail.com
Li Wang
Publisher: Springer Nature, Switzerland
Language: English
ISBN: 978-3-030-71880-0
Edition: 1/e
Books Review
Publish Year: 2021
Pages: 188, Illustrated
Price: € 139,09
Professor Ching-Chang Ko, DDS, MS, PhD, Vig / William Endowed Chair of the Division of
Orthodontics, College of Dentistry at Ohio State University, Columbus, OH, USA, Professor
Dinggang Shen, PhD, FIEEE, FAIMBE, FIAPR, Dean of School of Biomedical Engineering at
ShanghaiTech University, Shanghai, China, and Assistant Professor Li Wang, BS, PhD, Department
of Radiology and Biomedical Research Imaging Center at the University of North Carolina at
Chapel Hill, Chapel Hill, NC, USA offer a new book in the field of artificial intelligence (AI) which
is an update in contemporary dentistry on aspects related to Machine Learning in Dentistry
(MLD), clearly explaining dental imaging, oral diagnosis and treatment, dental models and dental
research.
Today in dentistry, digital technologies such as conical beam computed tomography (CBCT),
intraoral 3D scanning, 3D printing and personalized treatment planning play an important role in
both research and practice.
The book entitled Machine Learning in Dentistry is divided in four parts, being written by a
series of invited experts who fill the fourteen chapters.
The five chapters in the first part, Machine Learning for Dental Imaging, present one by one, CBCT
segmentation of craniomaxillofacial bony structures, craniomaxillofacial landmark digitization
of 3D imaging, segmenting bones from brain MRI via generative adversarial learning, sparse
dictionary learning for 3D craniomaxillofacial skeleton estimation based on 2D face photographs
and facial recognition in orthodontics.
The four chapters in the second part, Machine Learning for Oral Diagnosis and Treatment Planning,
in four chapters, inform the reader on performing orthodontic diagnoses and treatment planning,
on a new approach to the extraction decision in orthodontics, characterization of craniofacial
variations and on patient-specific reference model for planning orthognathic surgery.
The two chapters in third part, Machine Learning and Dental Designs, are a detailed presentation
of aspects regarding orthodontic CAD / CAM technologies and assessment of outcomes by using
machine learning.
The three chapters in the last part, Machine Learning Supporting Dental Research, bring clarifica-
tions on evidence synthesis research, genetics and genomics and finite element modeling.
The book Machine Learning in Dentistry is a valuable guide for practitioners and researchers
in the field of dentistry who want to benefit from the contribution of using machine learning
techniques in their daily work. With the help of digital technologies, the treatment is more
predictable, objective and effective, reducing iatrogenic complications.
https://doi.org/10.25241/stomaeduj.2021.8(4).bookreview.2
The Books Review is drafted in the reviewer’s sole wording and illustrates his opinions
280 Stoma Edu J. 2021;8(4):280 pISSN 2360-2406; eISSN 2502-0285