TY  - INPR
JF  - Progress in Retinal and Eye Research
KW  - Artificial intelligence
KW  -  Big data
KW  -  Disease detection
KW  -  Disease prediction
KW  -  Oculomics
KW  -  Retinal imaging
KW  -  Systemic diseases
A1  - Zhu, Zhuoting
A1  - Wang, Yueye
A1  - Qi, Ziyi
A1  - Hu, Wenyi
A1  - Zhang, Xiayin
A1  - Wagner, Siegfried K
A1  - Wang, Yujie
A1  - Ran, An Ran
A1  - Ong, Joshua
A1  - Waisberg, Ethan
A1  - Masalkhi, Mouayad
A1  - Suh, Alex
A1  - Tham, Yih Chung
A1  - Cheung, Carol Y
A1  - Yang, Xiaohong
A1  - Yu, Honghua
A1  - Ge, Zongyuan
A1  - Wang, Wei
A1  - Sheng, Bin
A1  - Liu, Yun
A1  - Lee, Andrew G
A1  - Denniston, Alastair K
A1  - Wijngaarden, Peter van
A1  - Keane, Pearse A
A1  - Cheng, Ching-Yu
A1  - He, Mingguang
A1  - Wong, Tien Yin
ID  - discovery10205883
N2  - The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics- the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging (?hardware?); 2) the availability of large studies to interrogate associations (?big data?); 3) the development of novel analytical methods, including artificial intelligence (AI) (?software?). Oculomics offers an opportunity to enhance our understanding of the interplay between the eye and the body, while supporting development of innovative diagnostic, prognostic, and therapeutic tools. These advances have been further accelerated by developments in AI, coupled with large-scale linkage datasets linking ocular imaging data with systemic health data. Oculomics also enables the detection, screening, diagnosis, and monitoring of many systemic health conditions. Furthermore, oculomics with AI allows prediction of the risk of systemic diseases, enabling risk stratification, opening up new avenues for prevention or individualized risk prediction and prevention, facilitating personalized medicine. In this review, we summarise current concepts and evidence in the field of oculomics, highlighting the progress that has been made, remaining challenges, and the opportunities for future research.
SN  - 1350-9462
PB  - Elsevier BV
UR  - https://doi.org/10.1016/j.preteyeres.2025.101350
N1  - © The Author(s), 2025. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/
TI  - Oculomics: Current Concepts and Evidence
AV  - public
Y1  - 2025/03/04/
ER  -