Dementia is a progressive condition that affects memory, communication, and cognitive abilities by disrupting how brain cells function. It impacts a significant portion of the aging population—roughly one in 14 people over 65 and one in six over 80. Alzheimer’s disease, the most common form of dementia, is often marked by memory loss, confusion, and difficulties with language and comprehension. While a cure remains out of reach, catching the condition early can make a substantial difference by allowing patients and families more time to plan, access treatment, and adapt.

The Role of Eye Tests in Dementia Research

A team of Scottish researchers is exploring a groundbreaking way to spot dementia before symptoms emerge. Their focus is on retinal imaging—photographs of the back of the eye—an area that shares many similarities with the brain’s vascular system. By using artificial intelligence to analyze these images, the team aims to detect biological markers of neurological disease in its earliest stages. This effort forms part of the NeurEYE program, an initiative led by the University of Edinburgh in collaboration with Glasgow Caledonian University and supported by NHS Scotland.

Millions of anonymized eye scans collected by optometrists across Scotland will feed into a massive dataset. With this information, researchers can apply AI and machine learning to search for indicators of dementia and other neurological disorders. The project, backed by NEURii—a global partnership involving academic institutions, healthcare organizations, and private sector partners—seeks to combine cutting-edge medical research with scalable, real-world healthcare tools.

Using AI to Detect Early Cognitive Decline

The NeurEYE program has ambitious goals. By identifying new biomarkers for Alzheimer’s and similar conditions, it could help accelerate drug development, improve the selection of clinical trial candidates, and enhance monitoring of treatment effectiveness. Beyond the lab, the technology could eventually be integrated into routine eye exams at high-street opticians, allowing widespread, affordable access to dementia risk screening.

This approach also has the potential to serve as a triage tool, helping optometrists decide when to refer patients to specialized care. In cases where a dementia diagnosis has already been made, the AI system could track disease progression and measure responses to treatment more accurately than current methods.

Expert Perspectives

Professor Baljean Dhillon of the University of Edinburgh points out that the retina offers a unique advantage: unlike the brain, it can be observed easily and non-invasively with equipment already available in many optometry practices. Meanwhile, Professor Miguel Bernabeu highlights how recent advances in AI have revolutionized the interpretation of medical images, making early disease prediction more realistic than ever before. Both emphasize the importance of building AI systems with representative datasets to ensure that diagnostic tools are accurate, fair, and effective for all patients.

Looking Ahead

The NeurEYE initiative illustrates how artificial intelligence can redefine dementia detection. By pairing advanced machine learning with simple, accessible eye exams, this research could provide a practical, non-invasive method for identifying at-risk individuals well before symptoms appear. If successful, it will not only make early detection more accessible but also improve treatment planning, support drug development, and enhance long-term monitoring of cognitive decline.

This work underscores the power of cross-disciplinary collaboration and shows how technology, when thoughtfully applied, can transform healthcare delivery. For patients, families, and clinicians alike, AI-driven eye tests may represent a new frontier in the fight against dementia.