Assessing Changes in Diabetic Retinopathy Caused by Diabetes Mellitus and Glaucoma Using Support Vector Machines in Combination with Differential Evolution Algorithm

Anton, Nicoleta; Drăgoi, Elena Niculina; Târcoveanu, Filip; Ciuntu, Roxana Elena; Lisa, Cătălin; Curteanu, Silvia; Doroftei, Bogdan; Ciuntu, Bogdan Mihnea; Chiseliţă, D; Bogdănici, Camelia Margareta

doi:10.3390/app11093944

Cited by 13 publications

(7 citation statements)

References 23 publications

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“…The efficacy of the proposed approach is assessed by relating the numerical results with that of nine similar approaches, including conventional SVM [32], CSA-SVM [35], GA-SVM [41], PSO-SVM [42], Improved whale optimization algorithm-based SVM (IWOA-SVM) [43], Differential Evolution algorithm-based SVM (DE-SVM) [44], GWO-SVM [32], Enhanced GWO-based SVM (EGWO-SVM) [45], Augmented GWO-based SVM (AGWO-SVM) [46]. In this study, LIBSVM model introduced by Chang and Lin [47] is used to realize SVM.…”

Section: Resultsmentioning

confidence: 99%

A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System

Mallika

Selvamuthukumaran²

2021

Int J Comput Intell Syst

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Diabetes is an extremely serious hazard to global health and its incidence is increasing vividly. In this paper, we develop an effective system to diagnose diabetes disease using a hybrid optimization-based Support Vector Machine (SVM).The proposed hybrid optimization technique integrates a Crow Search algorithm (CSA) and Binary Grey Wolf Optimizer (BGWO) for exploiting the full potential of SVM in the diabetes diagnosis system. The effectiveness of our proposed hybrid optimization-based SVM (hereafter called CS-BGWO-SVM) approach is carefully studied on the real-world databases such as UCIPima Indian standard dataset and the diabetes type dataset from the Data World repository. To evaluate the CS-BGWO-SVM technique, its performance is related to several state-of-the-arts approaches using SVM with respect to predictive accuracy, Intersection Over-Union (IoU), specificity, sensitivity, and the area under receiver operator characteristic curve (AUC). The outcomes of empirical analysis illustrate that CS-BGWO-SVM can be considered as a more efficient approach with outstanding classification accuracy. Furthermore, we perform the Wilcoxon statistical test to decide whether the proposed cohesive CS-BGWO-SVM approach offers a substantial enhancement in terms of performance measures or not. Consequently, we can conclude that CS-BGWO-SVM is the better diabetes diagnostic model as compared to modern diagnosis methods previously reported in the literature.

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Section: Resultsmentioning

confidence: 99%

A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System

Mallika

Selvamuthukumaran²

2021

Int J Comput Intell Syst

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“…Previous studies have reported on VEGF, monocyte chemoattractant protein-1, TNF-α, transforming growth factor-β, and nicotinamide adenine dinucleotide phosphate oxidase as the markers of inflammation. L-citrulline, indoleacetic acid, chenodeoxycholic acid, and eicosapentaenoic acid have been reported as markers of metabolism[ 51 ]. SCG3 is an angiogenic factor restricted to pathological conditions in DR[ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Genipin relieves diabetic retinopathy by down-regulation of advanced glycation end products via the mitochondrial metabolism related signaling pathway

Sun,

Chen,

et al. 2023

World J Diabetes

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Diabetes and associated complications represent major global public health issues which are associated with impaired quality of life and premature death. Although some diabetic complications have decreased in the developed world, the majority are still prevalent, with an increasing trend in the developing world. Currently used therapies are mainly ‘glucocentric’, focusing on the optimization of glycemic control to prevent, delay or manage diabetes-associated complications- other common comorbidities, such as dyslipidemia and hypertension are often underestimated. Although a number of novel therapeutic approaches have been reported recently, some of them have not received comparable attention in relation to either further studies or potential clinical implementation. This editorial briefly discusses some recent therapeutic approaches to the prevention and management of diabetes and its associated complications, as well as potential directions for future research and development in this area.

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“…A comparison can also be made with the results obtained in [ 31 ] because the same dataset was used in order to solve the same problem. The method applied for the prediction of diabetic retinopathy included support vector machines, designed with an evolutionary algorithm, respectively the Differential Evolution algorithm.…”

Section: Discussionmentioning

confidence: 99%

Classification Algorithms Used in Predicting Glaucoma Progression

et al. 2022

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In this paper, various machine learning algorithms were used in order to predict the evolution of open-angle glaucoma (POAG). The datasets were built containing clinical observations and objective measurements made at the Countess of Chester Hospital in the UK and at the “St. Spiridon” Hospital of Iași, Romania. Using these datasets, different classification problems were proposed. The evaluation of glaucoma progression was conducted based on parameters such as VFI (Visual field index), MD (Mean Deviation), PSD (Pattern standard deviation), and RNFL (Retinal Nerve Fiber Layer). As classification tools, the following algorithms were used: Multilayer Perceptron, Random Forest, Random Tree, C4.5, k-Nearest Neighbors, Support Vector Machine, and Non-Nested Generalized Exemplars. The best results, with an accuracy of over 90%, were obtained with Multilayer Perceptron and Random Forest algorithms. The NNGE algorithm also proved very useful in creating a hierarchy of the input values according to their influence (weight) on the considered outputs. On the other hand, the decision tree algorithms gave us insight into the logic used in their classification, which is of practical importance in obtaining additional information regarding the rationale behind a certain rule or decision.

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Assessing Changes in Diabetic Retinopathy Caused by Diabetes Mellitus and Glaucoma Using Support Vector Machines in Combination with Differential Evolution Algorithm

Cited by 13 publications

References 23 publications

A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System

A Hybrid Crow Search and Grey Wolf Optimization Technique for Enhanced Medical Data Classification in Diabetes Diagnosis System

Genipin relieves diabetic retinopathy by down-regulation of advanced glycation end products via the mitochondrial metabolism related signaling pathway

Classification Algorithms Used in Predicting Glaucoma Progression

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