Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Tooth Anatomy01:21

Tooth Anatomy

The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or grinding food.

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Community-based tuberculosis screening with computer-aided detection technology alone and in combination with point-of-care C-reactive protein testing: a paired screen-positive trial.

The Lancet. Infectious diseases·2026
Same author

Assessment of modifications to a blind-sweep ultrasound protocol for improved lower-uterus imaging by novice operators.

Scientific reports·2026
Same author

Hydrogels as Carriers for Periodontal Ligament Stem Cells in Bone Repair: A Systematic Review.

Tissue engineering. Part B, Reviews·2026
Same author

Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation Study.

JMIR medical informatics·2026
Same author

Development and Validation of AI System for Tooth Detection and Diagnosis in Dental Radiographs.

International dental journal·2026
Same author

Wear resistance of composite repairs: Direct vs. semi-direct techniques in simulated oral aging.

Dental materials : official publication of the Academy of Dental Materials·2026
Same journal

Artificial Intelligence in Caries Risk Assessment: Evaluating the Current Status of CAMBRA and Cariogram with Large Language Models.

Caries research·2026
Same journal

AI-Driven Decision Thresholds in Cariology: A Systematic Review of Lesion Stage Detection on Bitewing Radiographs.

Caries research·2026
Same journal

What is dental caries - and why we need fluoride.

Caries research·2026
Same journal

Does adolescent obesity influence caries increment among young adults? A 5-year cohort study in southern Brazil.

Caries research·2026
Same journal

Teaching Others, Reflecting Self: Does Educating Patients Impact Students' Own Plaque Control?

Caries research·2026
Same journal

Deep Caries Management: EFCD-ESE-ORCA S3-Level Clinical Practice Guideline.

Caries research·2026
查看所有相关文章

相关实验视频

Updated: Jun 19, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.7K

基于深度学习的算法,用于分阶段测试咬翅的次要.

Niels van Nistelrooij1,2, Eduardo Trota Chaves3,4, Maximiliano Sergio Cenci3

  • 1Department of Oral and Maxillofacial Surgery, Radboud University Medical Center, Nijmegen, The Netherlands.

Caries research
|October 29, 2024
PubMed
概括
此摘要是机器生成的。

这项研究开发了一种人工智能算法,用于检测牙修复周围的二次. 卷积神经网络 (CNN) 在识别这些病变方面具有很高的准确性,有助于临床决策.

关键词:
人工智能的人工智能是人工智能.脏病检测 脏病检测卷积神经网络是一种卷积神经网络.诊断成像诊断成像的使用放射学 放射学 放射学 放射学

更多相关视频

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
09:10

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

2.8K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

774

相关实验视频

Last Updated: Jun 19, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.7K
Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans
09:10

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

2.8K
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

774

科学领域:

  • 人工智能在牙科中的应用
  • 牙科放射学 牙科放射学
  • 机器学习用于医学成像

背景情况:

  • 有限的人工智能工具可用于检测和分期二次.
  • 二次性牙是围绕牙科修复的重大临床挑战.

研究的目的:

  • 开发一种基于卷积神经网络 (CNN) 的算法,用于检测和分期二次.
  • 使用一种新的方法来确定病变的严重程度.

主要方法:

  • 训练了一个口罩R-CNN与Swin变压器在2,612个牙上恢复了咬伤翼X射线图.
  • 员工进行两阶段培训,以加强检测和严重性评估.
  • 使用专家注释和统计指标验证算法性能.

主要成果:

  • 实现了检测所有病变 (0.966 ± 0.025) 和牙病变 (0.964 ± 0.019) 的高特异性.
  • 演示了算法和专家严重程度得分之间的强相关性 (0.802).
  • 在ROC曲线下的面积为所有病变的0.940和牙病变的0.946.

结论:

  • 开发了一种改进的AI算法,以帮助临床医生检测和分期二次.
  • 该算法采用了创新的注释方法,将病变严重程度视为连续结果.
  • 这个工具支持更好的临床决策在修复性牙科.