NCT05231174已完成不适用
Efficacy of Using Large Language Model to Assist in Diabetic Retinopathy Detection
Sun Yat-sen University1 个研究点 分布在 1 个国家目标入组 535 人开始时间: 2023年5月1日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 535
- 试验地点
- 1
- 主要终点
- AUROC of the self-evaluation tool
研究概览
简要总结
With the increase in population and the rising prevalence of various diseases, the workload of disease diagnosis has sharply increased. The accessibility of healthcare services and long waiting times have become common issues in the public health medical system, with many primary patients having to wait for extended periods to receive medical services. There is an urgent need for rapid, accurate, and low-cost diagnostic services.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •The study will include adults aged 18 years and above who have been diagnosed with Type 2 diabetes but have not previously been screened for DR. Participants must demonstrate good compliance with clinical examinations, and provide informed consent.
排除标准
- •The study will exclude patients who have previously been diagnosed with DR, those who have recently undergone eye surgery, and those with other significant eye diseases that could potentially confound the results of DR screening. Individuals with ocular, auditory, or cognitive impairments that prevent the use of mobile phones or reading will also be excluded.
结局指标
主要结局
AUROC of the self-evaluation tool
时间窗: Immediately after using the chatbot
The performance of the self-evaluation tool is evaluated with accuracy with reference to the diagnostic labels by senior ophthalmologists based on fundus photos.
次要结局
未报告次要终点
研究者
Yingfeng Zheng
Professor
Sun Yat-sen University
研究点 (1)
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