The Studies of Early Intelligent Diagnosis of Limb Deformity in Children by AI and Clinic Application
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 9,000
- 主要终点
- Deformity detection
研究概览
简要总结
The limb deformity in children include congenital limb malformations or acquired from the damage of epiphyseal plate which caused by tumor, inflammation and trauma. Due to the complexity of the disease itself, rapid dynamic development and the characteristics of children's growth and development, the deformities are constantly changing. In addition, the serious lack of clinical diagnosis and treatment resources in the Department of Pediatric Orthopedics has led to the misdiagnosis and improper treatment of children's limb deformities. Thus, its necessary to find an intelligent way to help doctor to early diagnosis of limb deformity and provide a proper treatment in children.
详细描述
The extraction and application of big data of children's limb deformities, intelligent labeling of image data, precise positioning, and perfecting the anatomical data of children's limb deformities.Improve the positioning accuracy of key points in X-ray images of children's limb deformities by means of step-by-step supervision to improve the accuracy of diagnosis.Realize an intelligent report generation system that combines patient background information, establish an end-to-end auxiliary diagnosis and treatment suggestion demonstration application system; realize a full set of artificial intelligence solutions for children's skeletal deformities, early screening and diagnosis of children, and forming an intelligent referral system of children's limb deformities.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- — 至 18 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Children with limb deformity
排除标准
- •Children without limb deformity
结局指标
主要结局
Deformity detection
时间窗: At enrollment
It is a binary variable (1/0). The radiographic features of children would be evaluated by artificial Intelligence. If the deformity was detected, variable would be setted into 1.
次要结局
未报告次要终点