Transformative applications of oculomics-based AI approaches in the management of systemic diseases: A systematic review

作者：Zhongwen Li, Shiqi Yin, Shihong Wang, Yangyang Wang, Wei Qiang, Jiewei Jiang · 发表于：Journal of Advanced Research · 年份：2024 · DOI：10.1016/j.jare.2024.11.018 · 被引用次数：11 · 研究领域：Retinal Imaging and Analysis、Retinal Diseases and Treatments、Retinal and Optic Conditions

• Oculomics-based AI systems show robust performance in predicting systemic diseases. • Oculomics-based AI systems can be applied to monitor systemic diseases. • Oculomics-based AI systems are simple, cost-effective, and non-invasive methods. • Oculomics-based AI systems have the potential to reduce the mortality of systemic diseases. • Oculomics-based AI systems revolutionize the management of systemic diseases. Systemic diseases, such as cardiovascular and cerebrovascular conditions, pose significant global health challenges due to their high mortality rates. Early identification and intervention in systemic diseases can substantially enhance their prognosis. However, diagnosing systemic diseases often necessitates complex, expensive, and invasive tests, posing challenges in their timely detection. Therefore, simple, cost-effective, and non-invasive methods for the management (such as screening, diagnosis, and monitoring) of systemic diseases are needed to reduce associated comorbidities and mortality rates. This systematic review examines the application of artificial intelligence (AI) algorithms in managing systemic diseases by analyzing ophthalmic features (oculomics) obtained from convenient, affordable, and non-invasive ophthalmic imaging. Our analysis demonstrates the promising accuracy of AI in predicting systemic diseases. Subgroup analysis reveals promising capabilities of oculomics-based AI for disease staging, while caution is warranted due to the possible overes...