共 17 条
Predictive models of aging of the human eye based on ocular anterior segment morphology
被引:8
作者:
Ma, Jiaonan
[1
]
Xu, Xueli
[2
]
Li, Mengdi
[1
]
Zhang, Yan
[1
]
Zhang, Lin
[3
]
Ma, Ping
[4
]
Hou, Jie
[5
]
Lei, Yulin
[5
]
Liu, Jianguo
[6
]
Huangfu, Xiaojin
[7
]
Yang, Yang
[8
]
Yi, Xianglong
[9
]
Cheng, George
[10
]
Bai, Ji
[11
]
Zhong, Xingwu
[12
]
Xu, Ximing
[2
,13
]
Wang, Yan
[1
,3
]
机构:
[1] Tianjin Med Univ, Clin Coll Ophthalmol, 4 Gansu Rd, Tianjin 300020, Peoples R China
[2] Nankai Univ, Sch Stat & Data Sci, Tianjin, Peoples R China
[3] Nankai Univ, Affiliated Eye Hosp, Tianjin Key Lab Ophthalmol & Visual Sci, Tianjin Eye Inst,Tianjin Eye Hosp, 4 Gansu Rd, Tianjin 300020, Peoples R China
[4] Univ Georgia, Dept Stat, Athens, GA 30602 USA
[5] Jinan Mingshui Eye Hosp, Dept Ophthalmol, Jinan, Shandong, Peoples R China
[6] Xian 4 Hosp, Xian, Shaanxi, Peoples R China
[7] 4th Peoples Hosp Shenyang, Shenyang, Liaoning, Peoples R China
[8] Yanan Hosp Kunming City, Kunming, Yunnan, Peoples R China
[9] Xinjiang Med Univ, Affiliated Hosp 1, Urumqi, Xinjiang, Peoples R China
[10] Hong Kong Laser Eye Ctr, Hong Kong, Peoples R China
[11] Daping Hosp, Chongqing, Peoples R China
[12] Sun Yat Sen Univ, Hainan Eye Hosp, Zhongshan Ophthalm Ctr, Haikou, Guangdong, Peoples R China
[13] Key Lab Med Data Anal & Stat Res Tianjin, Tianjin, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Aging;
Machine learning;
Eye;
Anterior segment;
Morphology;
AGE;
AGREEMENT;
D O I:
10.1016/j.jbi.2021.103855
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
Aging is a major risk factor for various eye diseases, such as cataract, glaucoma, and age-related macular degeneration. Age-related changes are observed in almost all structures of the human eye. Considerable individual variations exist within a group of similarly aged individuals, indicating the need for more informative biomarkers for assessing the aging of the eyes. The morphology of the ocular anterior segment has been reported to vary across age groups, focusing on only a few corneal parameters, such as keratometry and thickness of the cornea, which could not provide accurate estimation of age. Thus, the association between eye aging and the morphology of the anterior segment remains elusive. In this study, we aimed to develop a predictive model of age based on a large number of anterior segment morphology-related features, measured via the high-resolution ocular anterior segment analysis system (Pentacam). This approach allows for an integrated assessment of age-related changes in corneal morphology, and the identification of important morphological features associated with different eye aging patterns. Three machine learning methods (neural networks, Lasso regression and extreme gradient boosting) were employed to build predictive models using 276 anterior segment features of 63,753 participants from 10 ophthalmic centers in 10 different cities of China. The best performing age prediction model achieved a median absolute error of 2.80 years and a mean absolute error of 3.89 years in the validation set. An external cohort of 100 volunteers was used to test the performance of the prediction model. The developed neural network model achieved a median absolute error of 3.03 years and a mean absolute error of 3.40 years in the external cohort. In summary, our study revealed that the anterior segment morphology of the human eye may be an informative and non-invasive indicator of eye aging. This could prompt doctors to focus on age-related medical interventions on ocular health.
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