Evaluation of Diagnostic Accuracy of Artificial Intelligence in Treatment Planning for Non-growing Class II Cases
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 193
- 主要终点
- Accuracy of Artificial intelligence in choosing\predicting the best treatment modality
研究概览
简要总结
The goal of this observational study is to evaluate the diagnostic accuracy of artificial intelligence in non-growing class II cases. The main question it aims to answer is:
Is Artificial Intelligence (AI) accurate in choosing a treatment modality for non-growing class II cases -whether to camouflage or surgical treatment?
participants already undergone orthodontic treatment, their pre-treatment and post-treatment records will be collected from the archive of orthodontic department at Cairo university
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •cases of non-growing patients with class II malocclusion
排除标准
- •Growing patient with class II malocclusion
结局指标
主要结局
Accuracy of Artificial intelligence in choosing\predicting the best treatment modality
时间窗: from enrollment to the end of treatment at 1 year
次要结局
未报告次要终点
研究者
Israa Abuobieda Ibrahim Elbagari
Master Degree student at the department of orthodontics
Cairo University