A Deep Learning-based Indicator to Reveal Biological Age Using Lens Photographs
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 6,000
- 试验地点
- 1
- 主要终点
- The difference between LensAge and chronological age
研究概览
简要总结
Assessment of aging is central to health management. Compared to chronological age, biological age can better reflect the aging process and health status; however, an effective indicator of biological age in clinical practice is lacking. Human lens accumulates biological changes during aging and is amenable to a rapid and objective assessment. Therefore, the investigators will develop LensAge as an innovative indicator to reveal biological age based on deep learning using lens photographs.
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
- 20 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •ages from 20 to 100 years
- •have anterior segment photographs
- •have ophthalmic and physical examination records
排除标准
- •have a history of previous eye surgery, eye trauma, or ocular diseases that can cause complicated cataracts
- •baseline information missing
结局指标
主要结局
The difference between LensAge and chronological age
时间窗: Baseline
The age estimation models based on a convolutional neural network (CNN) using lens photographs will be used to generate LensAge. LensAge at the individual level will be calculated by averaging the results of all images corresponding to one individual. The difference between LensAge at the individual level and chronological age will be used to unveil an individual's aging process. A difference above 0 indicates an individual with a faster pace of aging than their peers of the same chronological age, while a difference below 0 indicates a slower pace of aging.
次要结局
- Correlation between the LensAge difference and age-related health parameters(Baseline)
- Mean error (ME) of the DL age estimation model.(Baseline)
- Mean absolute error (MAE) of the DL age estimation model.(Baseline)
- R-squared (R2) of the DL age estimation model.(Baseline)
研究者
Haotian Lin
Professor
Sun Yat-sen University