eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2025-02-20 18 March Spl Edition 191 202 10.13005/bpj/3081 64369 article Arvind Mewada 1 Sushil Kumar Maurya 2 Mohd. Aquib Ansari 1 School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India Department of Computer Science and Engineering, ITER, Siksha ’O’ Anusandhan University, Bhubaneswar, India Diabetes mellitus (DM) is a chronic metabolic disorder condition that requires continuous monitoring and early detection to prevent serious complications such as diabetic retinopathy (DR) and diabetic foot (DF) disease. In recent years, medical imaging technologies coupled with machine learning techniques have made progress in the automated detection of DM-related complications using retina or foot images. This article proposes a novel Ens-DRDF model that integrates the detection of diabetic retinopathy and diabetic foot ulcers using advanced machine learning and image processing techniques. The process involves removing the optic disc and blood vessels, followed by feature extraction, segmentation, and classification. Fuzzy clustering aids lesion differentiation, enhancing image quality for improved DR diagnosis. https://biomedpharmajournal.org/vol18marchspledition/seeing-beyond-advanced-image-and-thermal-analysis-for-early-detection-of-diabetic-retinopathy-and-diabetes/ Deep CNN Diabetic Retinopathy Fuzzy Clustering K-Nearest Neighbors (KNN) Medical Image Processing Retinal Lesion Detection