A Novel Approach to Diabetic Foot Ulcer Prediction: Pedographic Classification Using ELM-PSO

Most people with diabetes will experience diabetic foot ulcers (DFUs), which are surface sores on the foot, at some point in their diabetes journey. Infection and amputation are among the severe consequences that can result from DFUs that are not addressed. It is critical to discover foot ulcers early because the onset of diabetes is unpredictable. In this regard, the authors of this study offer a model for the purpose of making reliable predictions about the onset of foot ulcers. Model training, feature extraction, and preprocessing are all steps in a sequential process. Using mask-based segmentation, preprocessing improves picture quality and removes noise from the scanned raw RGB images. Training an ELM-PSO model, which outperforms traditional ELM and PSO algorithms, requires careful management of features and uses GLCM for feature extraction. The results show a substantial increase in precision, reaching a mark of 97.15%.