Artificial intelligence for caries and periapical periodontitis detection

医学 牙周炎 牙科 一致性(知识库) 根尖周炎 口腔正畸科 人工智能 计算机科学
作者
Shihao Li,Jialing Liu,Zirui Zhou,Zilin Zhou,Xiaoyue Wu,Yazhen Li,Shida Wang,Wen Liao,Sancong Ying,Zhihe Zhao
出处
期刊:Journal of Dentistry [Elsevier]
卷期号:122: 104107-104107 被引量:44
标识
DOI:10.1016/j.jdent.2022.104107
摘要

Periapical periodontitis and caries are common chronic oral diseases affecting most teenagers and adults worldwide. The purpose of this study was to develop an evaluation tool to automatically detect dental caries and periapical periodontitis on periapical radiographs using deep learning.A modified deep learning model was developed using a large dataset (4129 images) with high-quality annotations to support the automatic detection of both dental caries and periapical periodontitis. The performance of the model was compared to the classification performance of dentists.The deep learning model automatically distinguished dental caries with an F1-score of 0.829 and periapical periodontitis with an F1-score of 0.828. The comparison of model-only and expert-only detection performance showed that the accuracy of the fully automatic method was significantly higher than that of the young dentists. With deep learning assistance, the experts not only reached a higher diagnostic accuracy with an average F1-score of 0.7844 for dental caries and 0.8208 for periapical periodontitis compared to expert-only scenarios, but also increased inter-observer agreement from 0.585/0.590 to 0.726/0.713 for dental caries and from 0.623/0.563 to 0.752/0.740 for periapical periodontitis.Based on these experimental results, deep learning can improve the accuracy and consistency of evaluating dental caries and periapical periodontitis on periapical radiographs.Deep learning models can improve accuracy and consistency and reduce the workload of dentists, making artificial intelligence a powerful tool for clinical practice.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
刚刚
EvolDog完成签到,获得积分20
刚刚
1秒前
1秒前
木光完成签到,获得积分20
1秒前
牧尔芙完成签到 ,获得积分10
2秒前
神介.Tzx发布了新的文献求助10
2秒前
月月完成签到 ,获得积分10
3秒前
无心的枕头完成签到,获得积分10
5秒前
7秒前
Yangzx发布了新的文献求助10
7秒前
不爱胡椒发布了新的文献求助10
9秒前
墨痕mohen完成签到 ,获得积分10
9秒前
小小兔完成签到,获得积分20
10秒前
小马甲应助pjs采纳,获得10
10秒前
11秒前
yyyyyyy发布了新的文献求助10
12秒前
AN发布了新的文献求助10
13秒前
will完成签到,获得积分10
13秒前
17835152738发布了新的文献求助10
13秒前
柠木关注了科研通微信公众号
14秒前
kento应助科研通管家采纳,获得100
18秒前
Owen应助科研通管家采纳,获得10
18秒前
情怀应助科研通管家采纳,获得10
18秒前
丘比特应助科研通管家采纳,获得10
19秒前
墨墨发布了新的文献求助10
20秒前
tangt糖糖完成签到,获得积分10
20秒前
左丘冥完成签到,获得积分10
21秒前
答案。完成签到 ,获得积分10
21秒前
21秒前
Tonnyjing应助yyyyyyy采纳,获得10
22秒前
22秒前
路人丨安完成签到,获得积分10
23秒前
goodesBright应助令莞采纳,获得10
23秒前
23秒前
24秒前
25秒前
田様应助左丘冥采纳,获得10
25秒前
26秒前
93发布了新的文献求助10
28秒前
高分求助中
좌파는 어떻게 좌파가 됐나:한국 급진노동운동의 형성과 궤적 2500
Sustainability in Tides Chemistry 1500
TM 5-855-1(Fundamentals of protective design for conventional weapons) 1000
CLSI EP47 Evaluation of Reagent Carryover Effects on Test Results, 1st Edition 800
Cognitive linguistics critical concepts in linguistics 800
Threaded Harmony: A Sustainable Approach to Fashion 799
Livre et militantisme : La Cité éditeur 1958-1967 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3053642
求助须知:如何正确求助?哪些是违规求助? 2710842
关于积分的说明 7423746
捐赠科研通 2355391
什么是DOI,文献DOI怎么找? 1247143
科研通“疑难数据库(出版商)”最低求助积分说明 606239
版权声明 595992