Health-care Monitoring System Using Artificial Intelligence for Diabetic Skin Diseases

It is projected that computer-aided diagnoses using artificial intelligence (AI) with deep learning (DP) technology will assist in early disease detection to decrease the appearance of diabetic skin diseases. This research proposes a health-care monitoring system using AI to find the hidden problems in diabetic skin diseases that are not similar to other skin diseases. AI-based methods are introduced for detailed research, which determines the outcomes using advanced screening systems on dermatology images of humans. Researchers can also evaluate the current state of this field’s development and identify better future directions that might be studied. Our present research study demonstrates the workflow discussion within the three stages: diabetic skin diseases analysis, dermoscopic image analysis using preprocessing methods, and enhancement of screening system approaches using multitask learning (MTL) technique in AI with deep convolutional neural network. The proposed model has achieved the best and highest results with accuracy of 96.67%, specificity of 96.30%, and sensitivity of 92.31% in the proposed dermoscopic diagnosis systems. In the future, more advanced techniques are needed to understand and identify all types of hidden diabetic skin diseases.