AI-powered virtual eye: perspective, challenges and opportunities

TL;DR

This paper discusses the development of an AI-powered 'virtual eye' platform that simulates the eye's structure and function, highlighting its potential to revolutionize ophthalmic care and research.

Contribution

It presents a comprehensive development roadmap for a multimodal, multiscale AI model of the human eye, integrating recent advances in AI, imaging, and multiomics.

Findings

High-fidelity digital replica of the human eye is feasible with current AI technologies.

The virtual eye can enable personalized ophthalmic diagnostics and treatment.

Challenges include interpretability, ethics, and data management.

Abstract

We envision the "virtual eye" as a next-generation, AI-powered platform that uses interconnected foundation models to simulate the eye's intricate structure and biological function across all scales. Advances in AI, imaging, and multiomics provide a fertile ground for constructing a universal, high-fidelity digital replica of the human eye. This perspective traces the evolution from early mechanistic and rule-based models to contemporary AI-driven approaches, integrating in a unified model with multimodal, multiscale, dynamic predictive capabilities and embedded feedback mechanisms. We propose a development roadmap emphasizing the roles of large-scale multimodal datasets, generative AI, foundation models, agent-based architectures, and interactive interfaces. Despite challenges in interpretability, ethics, data processing and evaluation, the virtual eye holds the potential to revolutionize personalized ophthalmic care and accelerate research into ocular health and disease.