Applications of Artificial Intelligence in Orthodontics-An Overview and Perspective Based on the Current State of the Art

被引:13
作者
Kunz, Felix [1 ]
Stellzig-Eisenhauer, Angelika [1 ]
Boldt, Julian [2 ]
机构
[1] Univ Hosp Wurzburg, Dept Orthodont, D-97070 Wurzburg, Germany
[2] Univ Hosp Wurzburg, Dept Prosthet Dent, D-97070 Wurzburg, Germany
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 06期
关键词
orthodontics; artificial intelligence; machine learning; deep learning; cephalometry; age determination by skeleton; tooth extraction; orthognathic surgery; CERVICAL VERTEBRAL MATURATION; SKELETAL MATURATION; DECISION-MAKING; NEURAL NETWORKS; CVM METHOD; EXTRACTION; CLASSIFICATION; DIAGNOSIS; AGE; RELIABILITY;
D O I
10.3390/app13063850
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Featured Application The aim of this article is to provide the reader with an overview of current applications of AI in orthodontics. Artificial intelligence (AI) has already arrived in many areas of our lives and, because of the increasing availability of computing power, can now be used for complex tasks in medicine and dentistry. This is reflected by an exponential increase in scientific publications aiming to integrate AI into everyday clinical routines. Applications of AI in orthodontics are already manifold and range from the identification of anatomical/pathological structures or reference points in imaging to the support of complex decision-making in orthodontic treatment planning. The aim of this article is to give the reader an overview of the current state of the art regarding applications of AI in orthodontics and to provide a perspective for the use of such AI solutions in clinical routine. For this purpose, we present various use cases for AI in orthodontics, for which research is already available. Considering the current scientific progress, it is not unreasonable to assume that AI will become an integral part of orthodontic diagnostics and treatment planning in the near future. Although AI will equally likely not be able to replace the knowledge and experience of human experts in the not-too-distant future, it probably will be able to support practitioners, thus serving as a quality-assuring component in orthodontic patient care.
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页数:10
相关论文
共 96 条
[31]   Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs [J].
Gulshan, Varun ;
Peng, Lily ;
Coram, Marc ;
Stumpe, Martin C. ;
Wu, Derek ;
Narayanaswamy, Arunachalam ;
Venugopalan, Subhashini ;
Widner, Kasumi ;
Madams, Tom ;
Cuadros, Jorge ;
Kim, Ramasamy ;
Raman, Rajiv ;
Nelson, Philip C. ;
Mega, Jessica L. ;
Webster, R. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2016, 316 (22) :2402-2410
[32]  
Han M, 2001, CANCER, V91, P1661, DOI 10.1002/1097-0142(20010415)91:8+<1661::AID-CNCR1180>3.0.CO
[33]  
2-5
[34]   Automated identification of cephalometric landmarks: Part 2-Might it be better than human? [J].
Hwang, Hye-Won ;
Park, Ji-Hoon ;
Moon, Jun-Ho ;
Yu, Youngsung ;
Kim, Hansuk ;
Her, Soo-Bok ;
Srinivasan, Girish ;
Aljanabi, Mohammed Noori A. ;
Donatelli, Richard E. ;
Lee, Shin-Jae .
ANGLE ORTHODONTIST, 2020, 90 (01) :69-76
[35]   Extraction frequencies at a university orthodontic clinic in the 21st century: Demographic and diagnostic factors affecting the likelihood of extraction [J].
Jackson, Tate H. ;
Guez, Camille ;
Lin, Feng-Chang ;
Proffit, William R. ;
Ko, Ching-Chang .
AMERICAN JOURNAL OF ORTHODONTICS AND DENTOFACIAL ORTHOPEDICS, 2017, 151 (03) :456-462
[36]   New approach for the diagnosis of extractions with neural network machine learning [J].
Jung, Seok-Ki ;
Kim, Tae-Woo .
AMERICAN JOURNAL OF ORTHODONTICS AND DENTOFACIAL ORTHOPEDICS, 2016, 149 (01) :127-133
[37]   Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making - A systematic review [J].
Khanagar, Sanjeev B. ;
Al-Ehaideb, Ali ;
Vishwanathaiah, Satish ;
Prabhadevi, C. ;
Patil, Shankargouda ;
Naik, Sachin ;
Baeshen, Hosam A. ;
Sarode, Sachin S. .
JOURNAL OF DENTAL SCIENCES, 2021, 16 (01) :482-492
[38]   Evaluation and comparison of smartphone application tracing, web based artificial intelligence tracing and conventional hand tracing methods [J].
Kilinc, Delal Dara ;
Kircelli, Beyza Hancioglu ;
Sadry, Sanaz ;
Karaman, Ahmet .
JOURNAL OF STOMATOLOGY ORAL AND MAXILLOFACIAL SURGERY, 2022, 123 (06) :E906-E915
[39]   Prediction of hand-wrist maturation stages based on cervical vertebrae images using artificial intelligence [J].
Kim, Dong-Wook ;
Kim, Jinhee ;
Kim, Taesung ;
Kim, Taewoo ;
Kim, Yoon-Ji ;
Song, In-Seok ;
Ahn, Byungduk ;
Choo, Jaegul ;
Lee, Dong-Yul .
ORTHODONTICS & CRANIOFACIAL RESEARCH, 2021, 24 :68-75
[40]   Web-based fully automated cephalometric analysis by deep learning [J].
Kim, Hannah ;
Shim, Eungjune ;
Park, Jungeun ;
Kim, Yoon-Ji ;
Lee, Uilyong ;
Kim, Youngjun .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2020, 194