Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Public
health in Sri Lanka has considerable obstacles due to the prevalence of
undiagnosed diabetes and a lack of awareness of diabetic diseases. Many people
do not become aware of having diabetes until it's already had terrible effects.
In this study, we present a mobile application that uses image processing and
machine learning techniques to identify and track common skin diseases linked
to diabetes, such as cellulitis, Acanthosis nigricans, nail abnormalities, and
foot ulcers. The mechanisms that are already in place exclusively concentrate
on foot ulcers, ignoring other significant illnesses. By giving users a way to
evaluate their diabetes and spot potential skin infections through changes to
their body or skin, the smartphone application intends to empower people with
diabetes. People can seek appropriate treatment, lower their risk of
complications, and possibly save lives by quickly identifying these illnesses.
The suggested solution calls for specific domain knowledge in dermatology,
medical imaging, image processing, and machine learning. This study intends to
improve diabetes care and the avoidance of diabetic skin infections by
addressing the limitations in current detection systems.
Country : Sri Lanka
IRJIET, Volume 7, Issue 11, November 2023 pp. 335-342