17 Sep 2025: Modern technology and Artificial Intelligence (AI) are giving a new direction to the study of eyes and the field of ophthalmology. Today, with the help of AI and machine learning, analyzing retinal images can not only detect eye diseases but also identify several serious systemic health issues at an early stage.
The retina, the back part of the eye, provides a clear reflection of the blood vessels in the body. For this reason, it is considered an accurate indicator of the body’s vascular health.
According to a report published in Down To Earth, research has shown that narrowing of small blood vessels in the retina indicates long-term high blood pressure, while widening of large vessels may be linked to kidney problems in type 1 diabetes. Additionally, the arteriolar-to-venular diameter ratio serves as an important biomarker for stroke and heart disease. Regular retinal examinations can, therefore, help in timely detection of diabetes, kidney disease, heart problems, and even neurological disorders.
Over the past two decades, retinal fundus photography, optical coherence tomography angiography (OCT-A), and adaptive optics retinal imaging techniques have made it easier to capture high-resolution images of fine blood vessels in the eyes. These techniques are used to detect diabetic retinopathy, glaucoma, and age-related macular degeneration. Now, AI software can read these images and automatically analyze the condition of blood vessels and arteries.
Recently, a technology called Oculomics has raised new hope in understanding retinal microvascular biomarkers. AI can now learn from before-and-after images to predict outcomes of macular hole surgery, making surgical planning and patient counseling easier. In countries like India, where the number of diabetes patients is continuously increasing, AI-based non-invasive diabetes screening can be highly effective.
While current HbA1c tests require a blood sample, research teams are developing deep learning frameworks that can accurately estimate blood sugar levels (HbA1c) using just a single retinal image.
Another project is based on AC-GAN (Auxiliary Classifier Generative Adversarial Networks), which can detect multiple diseases simultaneously from retinal images. This allows doctors to perform early assessment of diabetes, heart disease, kidney problems, and other conditions in a single scan. However, AI-based healthcare approaches still face certain challenges.
Summary: Researchers claim AI technology can identify diabetes, kidney issues, and other diseases non-invasively by analyzing the eyes, eliminating the need for traditional needle-based blood tests.