Diabetic Foot Ulcer Identification using Machine Learning

Diabetic Foot Ulcer (DFU) is the main complexity of Diabetes, and might lead to cutoff of foot. One of the advancements of DFU treatment depends on the alertness of doctors and patients. This treatment approach has drawbacks such as the high cost of the diagnosis as well as the length of treatment. The analyzers had proposed many methods based on the technology which depends on both hardware as well as software (That includes sensors, portable devices, and deep learning algorithms). To have an efficient technique for diabetic foot ulcer detection, there is a need to enrich the process by deep learning and machine learning models to get high performance in the result. This study has used an image dataset of around 1500 images. The model is trained with advanced convolutional neural networks (CNN) of 11 layers with utmost 70 epochs with a best possible accuracy. The comparative analysis is done and result can be easily accessible by using a web application.