Performance of Deep Learning for Classifying level of surgical difficulty in impacted mandibular third molars
Completed
- Conditions
- Mandibular third molar which has Horizontal, Mesioangulation, Vertical angulation, and Distoangulation.Mandibular third molar
- Registration Number
- TCTR20221203001
- Lead Sponsor
- Department of Oral and Maxillofacial surgery ,faculty of dentistry chulalongkorn university
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Completed
- Sex
- All
- Target Recruitment
- 1000
Inclusion Criteria
1. Mandibular third molar which has Horizontal, Mesioangulation, Vertical angulation, and Distoangulation.
2. All Image file types are .bmp
3. The Panoramic radiograph has an appropriate quality for interpreting and scoring.
Exclusion Criteria
1. Age less than 18 years
2. Absence of the lower second molar
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Accuracy , sensitivity (SE), specificity (SP), and F-measure (FM) values for assessing program mandibular third molar segregation. at 3 months after end of the intervention . Confusion metric for multiclass classification
- Secondary Outcome Measures
Name Time Method Performance of the model 6 months Confusion metric