Dentronics: Towards robotics and artificial intelligence in dentistry

人工智能 机器人学 自动化 背景(考古学) 计算机科学 机器人 机器学习 人工智能应用 牙科 工程类 医学 机械工程 古生物学 生物
作者
Jasmin Grischke,Lars Johannsmeier,Lukas Eich,Leif Griga,Sami Haddadin
出处
期刊:Dental Materials [Elsevier BV]
卷期号:36 (6): 765-778 被引量:189
标识
DOI:10.1016/j.dental.2020.03.021
摘要

This paper provides an overview of existing applications and concepts of robotic systems and artificial intelligence in dentistry. This review aims to provide the community with novel inputs and argues for an increased utilization of these recent technological developments, referred to as Dentronics, in order to advance dentistry.First, background on developments in robotics, artificial intelligence (AI) and machine learning (ML) are reviewed that may enable novel assistive applications in dentistry (Sec A). Second, a systematic technology review that evaluates existing state-of-the-art applications in AI, ML and robotics in the context of dentistry is presented (Sec B).A systematic literature research in pubmed yielded in a total of 558 results. 41 studies related to ML, 53 studies related to AI and 49 original research papers on robotics application in dentistry were included. ML and AI have been applied in dental research to analyze large amounts of data to eventually support dental decision making, diagnosis, prognosis and treatment planning with the help of data-driven analysis algorithms based on machine learning. So far, only few robotic applications have made it to reality, mostly restricted to pilot use cases.The authors believe that dentistry can greatly benefit from the current rise of digital human-centered automation and be transformed towards a new robotic, ML and AI-enabled era. In the future, Dentronics will enhance reliability, reproducibility, accuracy and efficiency in dentistry through the democratized use of modern dental technologies, such as medical robot systems and specialized artificial intelligence. Dentronics will increase our understanding of disease pathogenesis, improve risk-assessment-strategies, diagnosis, disease prediction and finally lead to better treatment outcomes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
songYi完成签到,获得积分10
刚刚
小强同学发布了新的文献求助10
刚刚
1秒前
善良羿应助牧百川采纳,获得10
1秒前
acceptedsxy完成签到 ,获得积分10
1秒前
科研通AI2S应助yangyang2021采纳,获得10
2秒前
FashionBoy应助酷炫冷卉采纳,获得10
2秒前
3秒前
爱喝水的乌鸦完成签到 ,获得积分10
3秒前
宗晓凡发布了新的文献求助10
3秒前
3秒前
4秒前
狂野谷槐完成签到,获得积分10
4秒前
xina完成签到,获得积分20
4秒前
Serendipity完成签到,获得积分10
4秒前
yooloo发布了新的文献求助10
4秒前
浦肯野完成签到,获得积分0
4秒前
科研通AI6.4应助小小平采纳,获得10
5秒前
5秒前
思源应助1234采纳,获得10
5秒前
猫雪风晴完成签到 ,获得积分10
5秒前
5秒前
satan9完成签到,获得积分10
5秒前
6秒前
7秒前
7秒前
落寞的弘文完成签到,获得积分20
7秒前
指哪打哪完成签到,获得积分10
7秒前
皮灵犀发布了新的文献求助10
7秒前
7秒前
8秒前
边宇发布了新的文献求助20
8秒前
韦思诺完成签到,获得积分20
8秒前
大模型应助李光采纳,获得10
9秒前
9秒前
风铃草完成签到,获得积分10
9秒前
10秒前
明理雪晴发布了新的文献求助10
10秒前
三三三木发布了新的文献求助10
10秒前
Jude完成签到,获得积分10
10秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7239864
求助须知:如何正确求助?哪些是违规求助? 8865054
关于积分的说明 18700028
捐赠科研通 6911499
什么是DOI,文献DOI怎么找? 3195144
关于科研通互助平台的介绍 2367508
邀请新用户注册赠送积分活动 2169775