Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images

The advent of artificial intelligence (AI), especially the state-of-the-art deep learning frameworks, has begun a silent revolution in all medical subfields, including ophthalmology. Due to their specific microvascular and neural structures, the eyes are anatomically associated with the rest of the body. Hence, ocular image-based AI technology may be a useful alternative or additional screening strategy for systemic diseases, especially where resources are scarce. This review summarizes the current applications of AI related to the prediction of systemic diseases from multimodal ocular images, including cardiovascular diseases, dementia, chronic kidney diseases, and anemia. Finally, we also discuss the current predicaments and future directions of these applications.

Automated summary

The emergence of artificial intelligence, especially advanced deep learning frameworks, has caused a revolution in all medical fields, including ophthalmology. Ocular image-based AI technology, due to the unique microvascular and neural structures of the eyes, may serve as a valuable tool for predicting systemic diseases, especially in resource-limited settings. This review summarizes the current applications of AI in predicting systemic diseases using multimodal ocular images, including cardiovascular diseases, dementia, chronic kidney diseases, and anemia. The review also discusses the current challenges and future directions of these applications.