Asia-Pacific Journal of Ophthalmology, March 2022

Purpose

Despite the huge investment in health care, there is still a lack of precise and easily accessible screening systems. With proven associations with many systemic diseases, the eye could potentially provide a credible perspective as a novel screening tool. This systematic review aims to summarize the current applications of the ocular image-based artificial intelligence in the detection of systemic diseases and suggest future trends for systemic disease screening.

Methods

A systematic search was conducted on September 1, 2021, using 3 databases—PubMed, Google Scholar, and Web of Science library. Date restrictions were not imposed and search terms covering ocular images, systemic diseases, and artificial intelligence aspects were used.

Results

Thirty-three papers were included in this systematic review. A spectrum of target diseases was observed, and this included but was not limited to cardio-cerebrovascular diseases, central nervous system diseases, renal dysfunctions, and hematological diseases. Additionally, one-third of the papers included risk factor predictions for the respective systemic diseases.

Conclusions

Ocular image-based artificial intelligence possesses potential diagnostic power to screen various systemic diseases and has also demonstrated the ability to detect Alzheimer’s and chronic kidney diseases at early stages. Further research is needed to validate these models for real-world implementation.