How a Bengaluru professor turned eye scans into AI-powered diagnostic tools

In multiple hospitals and thousands of homes, people are being screened and monitored without needles, wires, or disruption to their daily lives. A researcher in India’s tech capital is quietly reshaping how patients are screened and monitored, using tools that work without needles, wires, or even direct contact. Abhishek Appaji, an academic-turned-innovator, has built a suite of AI-led diagnostic systems, from retinal scans to portable digital X-ray systems, that are now in use across multiple hospitals. The work sits at the intersection of artificial intelligence, medical devices, and public health, areas where India is trying to build both scale and affordability.

From eye to brain
At the centre of Appaji’s research, his team has developed an AI-based retinal imaging system that analyses subtle patterns in the eye to flag potential neurological and psychiatric conditions, including disorders such as schizophrenia and bipolar disorder.

Traditional diagnosis in these areas often depends on long clinical interviews and specialist availability, both of which are limited in many parts of India. By contrast, retinal scans are quick, non-invasive, and relatively low-cost. The aim is not to replace clinicians, but to give them an early screening tool that can scale.


Portable diagnostics for underserved regions
Another piece of the puzzle is mobility. Appaji, a senior member of the IEEE, has also worked on portable digital X-ray systems designed for emergency use and rural healthcare environments, where access to full-scale imaging infrastructure is often limited.

These devices aim to cut diagnosis time in critical situations while extending imaging access beyond large urban hospitals. For his efforts, Appaji has also been honored with the prestigious IEEE Theodore W. Hissey Outstanding Young Professional Award.

Moving from research to deployment
The wider significance of this development lies in the transition from academic research to practical use. In India, many healthcare innovations remain confined to pilot stages or controlled environments. Deployment across hundreds of hospitals suggests a degree of institutional acceptance, though detailed outcome data is still evolving.

A broader trend in healthcare technology
The use of AI in diagnostics and patient monitoring has expanded steadily in recent years, particularly after the pandemic accelerated digital adoption in healthcare. Non-invasive tools are drawing attention for their potential to lower costs and improve accessibility, especially in regions with limited medical infrastructure.

India’s healthcare system continues to face gaps in access, affordability, and specialist availability. AI-led, non-invasive tools are increasingly being seen as one way to bridge these divides, particularly in tier-2 and rural markets.

However, experts continue to flag challenges around validation, data privacy, and regulatory oversight. Questions also remain on how such tools perform across diverse patient populations and clinical conditions.

For now, the spread of systems such as these points to a gradual shift in how hospitals are incorporating technology, less as standalone innovations and more as part of routine care processes.