(qlmbusinessnews.com . Tue 10th Jun, 2025) London, UK —
Revolutionizing Eye Care: The Impact of Artificial Intelligence on Diabetic Retinopathy Screening
In the second instalment of a six-part series exploring the impact of artificial intelligence (AI) on medical research and treatments, we delve into the transformative power of AI in tackling diabetic retinopathy, a condition faced by Terry Quinn, a West Yorkshire resident, who was diagnosed with diabetes in his teens. Initially, Quinn, like many, struggled to accept the frequent testing and the label of being diabetic. His greatest fear was amputation, not foreseeing the significant threat to his vision until he encountered bleeding in his eye, indicative of diabetic retinopathy – damage caused by diabetes to the retina's blood vessels, necessitating laser treatments followed by injections.
Despite these interventions, Quinn's sight deteriorated, impacting his daily life drastically and leading to emotional turmoil. A turning point in his journey came with the support from the Guide Dogs for the Blind Association, pairing him with Spencer, a black Labrador, who Quinn credits as his lifesaver. Now an advocate and fundraiser for the association, Quinn remains hopeful for advancements in early detection and treatment, expressing that he would have eagerly embraced AI technology had it been available to him.
In the UK, the NHS advocates for diabetic eye screenings biennially, contrasting with the US, where immediate and annual screenings post-diagnosis for type 2 diabetes are advised, despite not always being adhered to in practice, contributing to preventable vision loss. The challenges of accessibility, including costs and logistical barriers, are highlighted by Roomasa Channa, a retina specialist in the US, suggesting easier access to screenings could benefit patients.
AI presents a promising solution to these challenges, with its capability to swiftly and economically interpret fundus images, crucial for detecting diabetic retinopathy. Systems developed by companies like Retmarker in Portugal harness AI to flag potential concerns for further human analysis. João Diogo Ramos, CEO of Retmarker, notes the resistance to change as a significant barrier to the broader acceptance of AI diagnostics, despite independent studies validating the accuracy and efficiency of AI-powered systems like Retmarker Screening and Eyenuk’s EyeArt, balancing the nuances of sensitivity and specificity.
Google Health's venture into AI diagnostics has revealed both potential and limitations, with varying performances across different settings, underscoring the necessity for robust data and inclusivity in technological development. Nevertheless, the company is moving forward, licensing its model in Thailand and India, and partnering with Thai public health authorities to evaluate its cost-effectiveness, paving the way for broader implementation.
Comparative studies in Singapore on the economics of diabetic retinopathy screening models advocate for a hybrid approach, blending AI with human oversight, slated for integration into Singapore's national health IT platform by 2025. Yet, the global applicability and cost-effectiveness of AI tools remain uneven, with significant potential in wealthier nations and certain middle-income countries, but broader challenges persist.
The quest for equitable health outcomes, particularly for under-served communities, is echoed by Bilal Mateen, chief AI officer at PATH, and Dr. Channa, emphasizing the need to bridge health equity gaps. While AI offers a beacon of hope for routine diabetic eye disease detection, it should not overshadow the importance of comprehensive eye care, given AI's current limitations in identifying conditions like myopia and glaucoma.
For patients like Quinn, the advent of AI in medical diagnostics represents a beacon of hope for early intervention, potentially altering the course of their conditions and improving quality of life, marking an exciting frontier in the application of technology to healthcare.
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