TCTR20230227003尚未招募不适用
A deep learning model for glaucoma diagnosis based on optical coherence tomography (OCT) : a multicenter study
适应症
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 500
研究概览
简要总结
暂无简介。
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18 Years 至 N/A (No limit)（—）
- 性别
- All
入选标准
- •1. Patients with age over 18 years old
- •2. Patients who diagnosed glaucoma 400 eyes
- •3. Normal subject without glaucoma 100 eyes
- •4. Each subject should have OCT result and HVF 24-2 result within the same period (not more than 6 months apart)
排除标准
- •1. Patients with ocular comorbidities which obscure OCT data gathering
- •2. OCT signal strength less than 6
- •3. Patient with other comorbidities which interfere HVF 24-2 result e.g. retinal disease or neuro-ophthalmologic disease
- •4. Unreliable HVF result (fixation loss > 20%, false positive > 20%, false negative > 20%, rim artifact, lid effect, clover leaf)
研究者
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