Diagnosis of In Vivo Vertical Root Fracture in Endodontically Treated Teeth Using Machine Learning Techniques
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CE Hours: 1.0
Description: This study aimed to diagnose vertical root fracture (VRF) of endodontically treated teeth using clinical features and bone loss information from cone beam computed tomography with machine learning models.
At the conclusion of this article, the reader will be able to:
- Explain why machine learning models for the diagnosis of VRF using age, sex, tooth type,the quality of root canal filling and bone loss position, height, width, and depth are valuable for clinical decision making after root canal treatment
- Describe how to diagnose vertical root fracture (VRF) of endodontically treated teeth using clinical features and bone loss information from cone beam computed tomography
- Explain the relationship between VRF and machine learning models
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Diagnosis of In Vivo Vertical Root Fracture in Endodontically Treated Teeth Using Machine Learning Techniques
Open to download resource.
Open to download resource.
Published 10/1/2025
Evaluation
8 Questions
8 Questions
CE Test
5 Questions | Unlimited attempts | 4/5 points to pass
5 Questions | Unlimited attempts | 4/5 points to pass
Certificate
1.00 CE credit | Certificate available
1.00 CE credit | Certificate available
Product Details
Shujun Ran, PhD
Qiang Wang, MEng
Jia Wang, PhD
Jing Huang, MD
Wei Zhou, MD
Pengfei Zhang, MS
Keyong Yuan, PhD
Yushan Cheng, MD
Shensheng Gu, PhD
Jingjing Zhu, MS