The development of orthognathic surgery in the age of artificial intelligence

doi:10.3877/cma.j.issn.1674-1366.2020.02.002

Chinese Journal of Stomatological Research(Electronic Edition) ›› 2020, Vol. 14 ›› Issue (02): 71-75. doi: 10.3877/cma.j.issn.1674-1366.2020.02.002

Special Issue: ；；

• Expert Opinions • Previous Articles Next Articles

The development of orthognathic surgery in the age of artificial intelligence

Yulin Shi¹, Jianglin Shi², Shizhu Bai³, Hongtao Shang¹, Lei Tian¹, Mingchao Ding¹, Yanpu Liu¹^,^†()

^1. National Key Laboratory of Military Stomatology & National Clinical Medical Research Center of Stomatology & Shaanxi Provincial Clinical Medical Research Center of Stomatology & Department of Stomatology Hospital of Air Force Military Medical University, Xi′an 710032, China
^2. Department of Control Engineering, School of Electronics and Information, Xi'an Jiaotong University, Xi′an 710049, China
^3. National Key Laboratory of Military Stomatology, National Clinical Medical Research Center of Stomatology, Shaanxi Province Clinical Medical Research Center of Stomatology, Department of Prosthodontics of Air Force Military Medical University, Xi′an 710032, China

Received:2020-01-13 Online:2020-04-01 Published:2020-04-01
Contact: Yanpu Liu
About author:
Corresponding author: Liu Yanpu, Email: liuyanpu@fmmu.edu.cn
Supported by:
National Key Research & Development (R & D) Plan Program(2017YFB1104100)

Abstract

Abstract:

This paper reviews the concept of artificial intelligence technology (AI) and its development in different times, summarizes the application of AI in medical field, reviews the research progress, existing problems and possible development direction of AI in orthognathic surgery, and points out that the development of AI in orthognathic surgery is full of opportunities and challenges.

Key words: Artificial intelligence, Orthognathic surgery

Yulin Shi, Jianglin Shi, Shizhu Bai, Hongtao Shang, Lei Tian, Mingchao Ding, Yanpu Liu. The development of orthognathic surgery in the age of artificial intelligence[J]. Chinese Journal of Stomatological Research(Electronic Edition), 2020, 14(02): 71-75.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhkqyxyjzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1674-1366.2020.02.002

https://zhkqyxyjzz.cma-cmc.com.cn/EN/Y2020/V14/I02/71

Figures/Tables 2

References 25

[1]	上海交通大学人工智能研究院，上海市卫生和健康发展研究中心，上海交通大学医学院，等.中国人工智能医疗白皮书[R/OL]. 2019. URL
[2]	Topol EJ. High-performance medicine：the convergence of human and artificial intelligence[J]. Nat Med，2019，25：44-56. DOI：10.1038/s4159-018-0300-7.
[3]	蔡自兴，徐光裕.人工智能及其应用[M]. 2版.北京：清华大学出版社，1996：8-172.
[4]	Hinton GE，Osindero S，Teh YW. A fast learning algorithm for deep belief nets[J]. Neural Comput，2006，18（7）：1527-1554. DOI：10.1162/neco.2006.18.7.1527.
[5]	Succi S，Coveney PV. Big data：the end of the scientific method？[J]. Philos Trans A Math Phys Eng Sci，2019，377（2142）：20180145. DOI：10.1098/rsta.2018.0145.
[6]	de Dombal FT，Leaper DJ，Staniland JR，et al. Computer-aided diagnosis of acute abdominal pain[J]. Br Med J，1972，2（5804）：9-13. DOI：10.1136/bmj.2.5804.9.
[7]	Banks G. Artificial intelligence in medical diagnosis：the INTERNIST/CADUCEUS approach[J]. Crit Rev Med Inform，1986，1（1）：23-54.
[8]	Shortliffe EH，Buchanan BG. A model of inexact reasoning in medicine[J]. Mathematical Biosciences，1975，23（3-4）：351-379. DOI：10.1016/0025-5564(75)90047-4.
[9]	Anderson JG，Jay SJ. Computers and clinical judgment：the role of physician networks[J]. Soc Sci Med，1985，20（10）：969-979. DOI：10.1016/0277-9536(85)90253-9.
[10]	Singh R，Kalra MK，Nitiwarangkul C，et al. Deep learning in chest radiography：detection of findings and presence of change[J]. PLoS ONE，2018，13（10）：e0204155. DOI：10.1371/journal.pone.0204155.
[11]	沈国芳，房兵.正颌外科学[M].杭州：浙江科学技术出版社，2013：4.
[12]	Patcas R，Bernini DAJ，Volokitin A，et al. Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age[J]. Int J Oral Maxillofacil Surg，2019，48（1）：77-83. DOI：10.1016/j.ijom.2018.07.010.
[13]	Choi HI，Jung SK，Baek SH，et al. Artificial Intelligent Model With Neural Network Machine Learning for the Diagnosis of Orthognathic Surgery[J]. J Craniofac Surg，2019，30（7）：1986-1989. DOI：10.1097/SCS.0000000000005650.
[14]	Knoops P，Papaioannou A，Borghi A，et al. A machine learning framework for automated diagnosis and computer-assisted planning in plastic and reconstructive surgery[J]. Sci Rep，2019，9（1）：13597. DOI：10.1038/s41598-019-49506-1.
[15]	Stehrer R，Hingsammer L，Staudigl C，et al. Machine learning based prediction of perioperative blood loss in orthognathic surgery[J]. J Cranio-Maxillofacial Surg，2019，47（11）：1676-1681. DOI：10.1016/j.jcms.2019.08.005.
[16]	Nadler SB，Hidalgo JH，Bloch T. Prediction of blood volume in normal human adults[J]. Surgery，1962，51（2）：224-232.
[17]	Solow B. Computers in cephalometric research[J]. Comput Biol Med，1970，1（1）：41-49. DOI：10.1016/0010-4825(70)90015-6.
[18]	Walker GF，Kowalski CJ. Use of angular measurements in cephalometric analyses[J]. J Dent Res，1972，51（4）：1015-1021. DOI：10.1177/00220345720510040401.
[19]	Mirzaalian H，Hamarneh G. Automatic globally-optimal pictorial structures with random decision forest based likelihoods for cephalometric X-Ray landmark detection[C]. International Symposium on Biomedical Imaging 2014：Automatic Cephalometric X-Ray Landmark Detection Challenge，2014：1-12.
[20]	Ibragimov B，Likar B，Pernus F，et al. Shape representation for efcient landmark-based segmentation in 3-D[J]. IEEE Transactions on Medical Imaging，2014，33（4）：861-874. DOI：10.1109/TMI.2013.2296976.
[21]	Chu C，Chen C，Nolte LP，et al. Fully automatic cephalometric X-Ray landmark detection using random forest regression and sparse shape composition[C]. International Symposium on Biomedical Imaging 2014：Automatic Cephalometric X-Ray Landmark Detection Challenge，2014：13-18.
[22]	Lindner C，Wang CW，Huang CT，et al. Fully automatic system for accurate localization and analysis of cephalometric landmarks in lateral cephalograms[J]. Scientifc Reports，2016，6：33581. DOI：10.1038/srep33581.
[23]	中国医学论坛报今日口腔.中国正畸医生的智慧：Uceph头影测量系统的研发及优势——王军教授[EB/OL].[2019-07-23]. URL
[24]	Olszewski R，Zech F，Cosnard G，et al. Three-dimensional computed tomography cephalometric craniofacial analysis：experimental validation in vitro[J]. Int J Oral Maxillofac Surg，2007，36（9）：828-833. DOI：10.1016/j.ijom.2007.05.022.
[25]	Swennen GR，Schutyser F，Barth EL，et al. A new method of 3-D cephalometry Part Ⅰ：the anatomic Cartesian 3-D reference system[J]. J Craniofac Surg，2006，17（2）：314-325. DOI：10.1097/00001665-200603000-00019.

Please choose a citation manager

Content to export

The development of orthognathic surgery in the age of artificial intelligence

RichHTML

PDF (PC)

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 2

References 25

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Meifang Zhang, Ying Tan, Qiaozhen Zhu, Xin Wen, Ying Yuan, Yue Qin, Hongbo Guo, Lingxiu Hou, Wenlan Huang, Guiyan Peng, Shengli Li. Artificial intelligence-based quality control of mid-sagittal plane ultrasound images for first trimester fetal crown-rump length [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2023, 20(09): 945-950.
[2]	Feifei Yang, Xixiang Lin, Yixin Chen, Qiushuang Wang, Liwei Zhang, Xu Chen, Meiqing Zhang, Shuhua Wang, Kunlun He. Automatic detection of regional wall motion abnormalities by echocardiography based on deep learning [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2023, 20(04): 424-429.
[3]	Wei Tang, Rongquan He, Suning Huang. Application of deep learning in imaging for diagnosis, treatment and prognosis prediction of breast cancer [J]. Chinese Journal of Breast Disease(Electronic Edition), 2023, 17(06): 323-328.
[4]	Shuaihua Fan, Wei Guo, Jun Guo. Current situation and prospect of application of decision tree algorithm based on machine learning in prognosis prediction of bloodstream infection [J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2023, 17(05): 289-293.
[5]	Hui Zhang, Min Cai, Xiangya Huang. Clinical application of digital technology and artificial intelligence in maxillary sinus floor augmentation [J]. Chinese Journal of Stomatological Research(Electronic Edition), 2023, 17(04): 244-252.
[6]	Xiaowei Xing, Yuchen Liu, Bing Zhao, Minggang Wang. A research on predictive value of convolutional neural network based on preoperative abdominal CT for recurrence of incisional hernia after surgical repair [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2023, 17(06): 677-681.
[7]	Xiaowei Xing, Yuchen Liu, Minggang Wang. Application and prospects of artificial intelligence technology in the field of hernia and abdominal wall surgery [J]. Chinese Journal of Hernia and Abdominal Wall Surgery(Electronic Edition), 2023, 17(04): 390-393.
[8]	Manshi Lei, Sisi Deng, Xinrong Wang, Jinbin Huang, Qing Xiang, Anni Xiong, Zhan'ao Meng. Application of artificial intelligence-assisted compression sensing technology in upper abdominal fat-suppressed T2WI sequence [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(05): 551-556.
[9]	Bing Han, Jinyang Gu. Research and application prospect of deep learning neural network in diagnosis and treatments for liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(05): 480-485.
[10]	Yunpeng Ge, Hongyuan Cui, Jinghai Song. Application of artificial intelligence in diagnosis, treatment and prognosis of primary liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(04): 367-371.
[11]	Xiaodong Wang, Kai Wang, Zhao Ge. Research progress of computer vision in improvement of therapeutic effect of liver transplantation for liver cancer [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(04): 361-366.
[12]	Ya Tian, Meilong Wu, Xiaobin Feng. Artificial intelligence in diagnosis and treatments for hepatocellular carcinoma [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(03): 258-262.
[13]	Jingke Li, Yanchun Zhang, Jiayi Wu, Xiuyu Ren. Deep learning for diabetic retinopathy screening, classification and management [J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2023, 13(04): 241-246.
[14]	Meiqi Ren, Junhong Li, Zhangqing Feng. Research progress on new hot issues of intermittent exotropia [J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2023, 13(03): 162-166.
[15]	Ping Hu, Tengfeng Yan, Haizhu Zhou, Xingen Zhu. Advances in artificial intelligence be applied to early diagnose intracranial hemorrhage and hematoma segmentation [J]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2023, 17(04): 410-416.

模态框（Modal）标题

Please choose a citation manager

Content to export

The development of orthognathic surgery in the age of artificial intelligence

RichHTML

PDF (PC)

Knowledge

Cited

Abstract

Cite this article

share this article

Figures/Tables 2

References 25

Related Articles 15

Recommended Articles

Metrics

Comments