Advancing Healthcare Access with AI in Remote Communities
A researcher at Heriot-Watt University is using artificial intelligence to improve access to medical diagnoses for patients living in remote areas. This innovative approach aims to provide timely and potentially lifesaving care, especially for those without easy access to dermatologists.
Tess Watt, a Ph.D. candidate in the School of Mathematical and Computer Sciences based in Edinburgh, has spent the past two years developing AI-driven tools to diagnose skin conditions, particularly skin cancer, in regions with limited medical infrastructure. Her work focuses on enabling early detection without requiring direct access to specialists, utilizing accessible technology that can be deployed anywhere from rural Scotland to West Africa.
“Health care from home is a really important topic at the moment, especially as GP wait times continue to grow,” said Watt. “If we can empower people to monitor skin conditions from their own homes using AI, we can dramatically reduce delays in diagnosis.”
Watt’s research is part of a broader collaborative effort involving academics from London South Bank University, Edinburgh Napier University, and the Foundation for Research and Technology—Hellas in Greece. It is considered the first project of its kind to combine AI medical diagnosis with the goal of serving remote communities.
A Prototype That Works Without Internet
A prototype of her system has already been demonstrated at Heriot-Watt’s advanced health and care technologies suite. The system uses AI to analyze images of skin lesions and flag potential risks for further medical review. What sets it apart is its ability to function without internet access.
The technology relies on low-cost Raspberry Pi devices, which act as portable computers that are energy efficient and capable of storing large amounts of information. Patients equipped with these devices can take a picture of their skin condition using a small camera attached to the Raspberry Pi. The image is analyzed in real-time using state-of-the-art image classification, comparing it to an extensive dataset of thousands of images to reach a diagnosis.
The findings are then shared with a local GP service to begin a suitable treatment plan. While the tool is currently up to 85% accurate, the team plans to increase this percentage by gaining access to more skin lesion datasets and using advanced machine learning models.
Future Plans and Collaborations
Although the technology has not yet been tested in real-world clinical settings, Watt is in discussions with NHS Scotland to begin the ethical approval process. She hopes to have a pilot project underway within the next year or two. Medical technology often takes years to move from prototype to implementation, so the timeline is realistic.
The long-term vision is to roll out the system first across remote regions of Scotland before expanding to global areas with limited access to dermatological care. It could also support patients who are infirm or unable to travel, allowing loved ones to assist with capturing and submitting diagnostic images to GPs.
Watt’s journey into healthcare AI was inspired by earlier work in accessible translation technologies. Combining this experience with her current studies in Tiny Machine Learning and research into underexplored areas of AI in medicine, she focused on dermatology.
“There’s a lot being done with AI and medical scans like X-rays and MRIs,” she said, “but relatively little using photographs of skin. I saw a real opportunity there.”
Ensuring Resilience in Health Care Technology
While deployment may still be years away, the relevance of her work is immediate. As health services across the U.K. struggle with backlogs and stretched resources, solutions that enable proactive, remote care are increasingly in demand. Watt’s research could represent a major step forward in both equity and efficiency for healthcare delivery.
Her academic supervisor, Dr. Christos Chrysoulas, emphasized the importance of robust system design in health care technology. He highlighted the need for e-health devices to operate independently of external connectivity to ensure continuity of patient service and safety.
“In the event of a network or cloud service failure, such devices must fail safely and maintain all essential clinical operations without functional degradation,” he said. “Ensuring this level of resilience in affordable, low-cost medical devices is the essence of our research, particularly for deployment in resource-limited settings.”
Expanding Global Impact
Watt’s work is part of Heriot-Watt’s wider ambitions through its Global Research Institute (GRI) in Health and Care Technologies. The institute is dedicated to advancing solutions for some of the world’s most critical health challenges.
It is already making significant progress with the launch of “One Health,” an established research theme within the GRI. This initiative addresses global health challenges such as infectious diseases, antimicrobial resistance (AMR), and emerging epidemics through the integration of human, animal, and environmental health.