… However, due to the increasing heterogeneity and lack of continuous monitoring, the early
diagnosis and classification of diabetes are often difficult in practice [5]. The majority of people …

… This paper describes a deep learning model able to detect medically interpretable … to classify
diabetes-related retinal diseases. Methods: This article presents a new deep learning model…

… To predict diabetes mellitus using deep learning, we follow the … (i) Data collection, (ii) Data
preparation, (iii) Implement deep … Class 1 indicate that the diabetes test is positive and class 0 …

… learning-based techniques with Deep Learning (DL) structures. We tested common structures
in the mode of transfer learning, … and DL for the classification of diabetic foot thermograms, …

… [16] deploy a deep learning model to detect the exudates in the retinal images. … the class
of every pixel. The model presented in this paper is developed using Tensorflow deep learning …

… such as cataracts as well as glaucoma, and we could enhance our model’s classification
performance by employing ensemble techniques of machine learning and deep learning. …

… papers related to DR classification. Overall, the focus of this paper highlights the prevalence
of Deep learning techniques for DR classification and its impact on classification results. …

… for the detection and classification of diabetic retinopathy on … of deep learning methods at
the various steps of the diabetic … , to the development of such deep learning models for the …

… [21] have used various DL models for the classification of … a deep learning-based technique
for detecting diabetic … proposed technique by gathering diabetic retinopathy data from …

… advances in deep learning 1,2 , particularly in the case of deep convolutional neural … diabetes
screening programmes and biobanks, cardiovascular risk factors, the presence of diabetic …