Validation of the Utility of Strabismus Intelligent Diagnostic System: A Clinical Trial
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 323
- 试验地点
- 1
- 主要终点
- The proportion of accurate, mistaken and miss detection of the diagnostic system.
研究概览
简要总结
Strabismus affects approximately 0.8%-6.8% of the world's population and appears by the age of 3 years in 65% of affected individuals. Manual measurement of deviation is often laborious and highly dependent on the experience of the specialist and the cooperation of the patients. Current strabismus evaluation technologies are heavily dependent on model eyes. Here, the investigators use deep learning to develop an artificial intelligence (AI) platform consisting of three deep learning (DL) systems to screen strabismus, evaluate deviation and propose a surgical plan based on corneal light-reflection photos. The investigator also conduct clinical trial to validate its versatility in clinical practice.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients in the outpatient clinic of strabismus department.
排除标准
- •Patients or their parents diagree to participate in the trial.
- •Patients with blepharoptosis.
- •Patients can't facing forward or lacking fixation.
研究组 & 干预措施
Eligible patients for AI test
Device: strabismus diagnostic system.
干预措施: Strabismus diagnostic system. (Drug)
结局指标
主要结局
The proportion of accurate, mistaken and miss detection of the diagnostic system.
时间窗: up to 3 years
次要结局
未报告次要终点
研究者
Haotian Lin
Clinical Professor
Sun Yat-sen University
