Comprehensive Summary
This study by Chou identifies four key requirements for real-world application of Al-based technology in diagnosing and screening retinal diseases: large dataset processing, ophthalmology practicability, policy compliance and regulatory environment, and cost-profit balancing. The Vision Academy, a group of over 100 international ophthalmologists, contributed to this study by providing suggestions based on their cumulative experience in clinical practice. Modern ophthalmology's reliance on imaging offers it a rich area for Al advances. However, constraints like proprietary devices, image-gathering methodologies, and data storage processes still need improvement.
Outcomes and Implications
AI may help reduce the labor shortage and bridge the gap between urban and rural healthcare services. The authors emphasize the importance of cross-functional collaboration, involving ophthalmologists, optometrists, data scientists, and patient organizations, to maximize the benefits of AI in vision health. The Vision Academy recommends leveraging AI as a complementary tool to current healthcare systems, enhancing decision-making and efficiency without compromising patient care. Key recommendations include: Striking a balance between data privacy and transparency to ensure ethical AI use, using AI to support accurate and timely decision-making rather than only improving workflow efficiency, and establishing specific regulatory bodies to verify AI models and address data security and legal liability concerns.