Beyond Vision: How AI is Predicting Eye Disease, Biological Age, Heart Disease, and Cancer

"AI has the potential to democratize eye care, providing access to those who might not otherwise be able to afford or reach it."

Artificial Intelligence is reshaping healthcare, and eye care is no exception. With the potential to democratize access, AI is opening doors for individuals who might not otherwise afford or reach essential eye care services. During my time as Chief Innovation Officer in the ophthalmology field, one of the most pressing challenges I saw was ensuring patient access to quality eye care, especially in underserved areas. As populations age and demand for eye care surges, the shortage of providers presents a critical bottleneck. This motivated me to research how AI could help bridge these gaps and extend quality care to those in need.

Today, AI is leading a significant transformation in ophthalmology, changing how we detect, diagnose, and treat eye conditions. Advanced AI tools are enhancing efficiency, precision, and accessibility, positioning eye care as one of the most forward-thinking fields in medicine. In this article, we'll explore how AI is driving groundbreaking advancements—from screening for diseases like diabetic retinopathy to predicting biological age, and even potentially identifying risk factors for conditions such as cardiovascular disease and cancer.

Leading AI Applications in Ophthalmology

Diabetic Retinopathy Screening - Companies like Eyenuk and Digital Diagnostics have introduced FDA-approved AI tools that autonomously detect diabetic retinopathy using retinal images. These tools significantly improve the speed and scale of screenings, allowing ophthalmologists to focus on treatment. At Johns Hopkins Medicine, AI-based screening has shown improved compliance rates for annual diabetic retinopathy checks compared to clinics without AI, highlighting its positive impact on patient care.

Age-Related Macular Degeneration (AMD) Management - Moorfields Eye Hospital and iHealthScreen AI is also making strides in managing AMD. At Moorfields Eye Hospital in London, an AI model developed by Balaskas has reduced the time for interpreting OCT scans (a noninvasive imaging method that uses reflected light to create pictures of the back of your eye) of geographic atrophy from 43 minutes to just 2 seconds, offering faster monitoring of patient response to therapeutics. iHealthScreen is seeking FDA clearance for iPredict, a tool designed for AMD screening, further expanding AI's capabilities in retinal care.

Latest Innovations and Collaborations

Geographic Atrophy Management - RetinAI has partnered with Boehringer Ingelheim to enhance AI’s role in managing geographic atrophy. RetinAI’s Discovery? platform aggregates and analyzes patient data, enabling improved disease monitoring and optimized treatment strategies. This collaboration demonstrates the potential of combining AI data platforms with pharmaceutical research for better patient outcomes.

Early Disease Detection - Eyetelligence now Optain (Australia) an Australian startup, raised $12 million to expand its AI tools globally. Bupa Optical uses its platform and is expanding to Europe and Japan. It enhances early disease detection and supports decision-making processes, showcasing how AI tools can be scaled to serve different regions.

Open-Source AI Model - RETfound by Moorfields Eye Hospital is an open-source AI model trained on over 1.6 million retinal images from Moorfields Eye Hospital. Developed by Pearse Keane at University College London, RETFound aims to democratize AI in ophthalmology. Researchers can adapt the model for various eye-related tasks, and it is being successfully used for multiple clinical applications worldwide.\

Other Emerging AI Players

AI Screening Programs— Byers Eye Institute at Stanford and Bascom Palmer Eye Institute have AI-driven screening programs. These initiatives focus on early detection of eye conditions such as glaucoma and AMD, particularly in underserved populations. AI tools in these settings are designed to predict disease progression, allowing for timely and personalized interventions.

Future Directions and Challenges

Leveraging AI for Biological Age Prediction and Personalized Healthcare

RetiAge by Oxford Academic The RetiAGE model uses retinal images to predict biological age, which has shown a strong correlation with health risks such as cardiovascular disease and cancer. Developed using deep learning, this model provides a non-invasive biomarker for assessing health and disease risk, with applications extending beyond ophthalmology into broader health prediction (Oxford Academic).

EyeAge by Google Health developed an "aging clock" called EyeAge that predicts biological age using retinal images. This model aims to reveal underlying biological conditions linked to aging, offering a new way to non-invasively assess individual health and genetic factors related to aging.

PhotoAgeClock by Insilico Medicine This tool predicts biological age by analyzing images of the skin around the eyes, a common indicator of aging. This AI system could be used for personalized medical interventions, skincare, and lifestyle assessments, expanding the role of AI in preventive healthcare (GlobalSpec).

AI in Broader Health Monitoring - Google Health AI also makes its mark in broader health monitoring. Google Health has been using eye images to predict systemic biomarkers, such as diabetes indicators, demonstrating the cross-disciplinary potential of AI. However, challenges like biases in AI models, data privacy concerns, and regulatory oversight remain key considerations for future development.

AI Streamlining Clinical Workflows - Bascom Palmer Eye Institute In clinical settings, AI streamlines workflows—from automating appointment scheduling to providing real-time insights through ambient scribe services. Bascom Palmer Eye Institute has utilized AI to tailor patient education to specific languages and reading levels, significantly enhancing patient interactions and engagement.

The Future is Bright

AI has carved out a critical role in ophthalmology, offering solutions that range from improved diagnostics to more personalized treatment pathways. Companies like Eyenuk, RetinAI, Moorfields Eye Hospital, and others are at the forefront of this transformation. AI has the potential to democratize eye care, providing access to those who might not otherwise be able to afford or reach it. I

If we can harness AI effectively, it could play a crucial role in shaping the future of global eye care, bridging the gaps in accessibility and affordability. As AI technologies continue to evolve, I am optimistic about their potential to revolutionize vision care and ensure equitable access to cutting-edge treatments worldwide, ultimately improving outcomes for patients everywhere.

By Andrew Livingston - Innovationwith.AI "Where Innovation meets AI"