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Research ArticleOpen accessIn the abstractTransforming Retinal Diagnostics: Advanced Detection of Diabetic Retinopathy Using Vision Transformers and Capsule NetworksVishal Sharma, Rishu, Vinay Kukreja et al.Diabetic Retinopathy (DR), nowadays is one of the leading causes of blindness worldwide, it is a severe complication of diabetes mellitus that affects the retina blood vessels. Accurate diagnosis depends on early detection of DR. The study aims to develop a hybrid model that is the combination of a Vision Transformer and Capsule Network (ViT-CapsNet) to classify the DR at … …Journal of Computer Science, Vol. 21, Issue 2 · 14 Jan 2025 · 6,765 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Mir 29c-3p and Mir 31-5p Serum Values in Predicting Nephropathy in Type 2 Diabetic PatientsMona S. Habieb, Nesreen Gamal Elhelbawy, Khaled M. Elzorkany et al.Diabetic Nephropathy (DN) is a prime complication of diabetes with various pathological mechanisms. microRNAs (miRNAs) have emerged as an important factor in the pathogenesis of renal disorders. We aimed to analyze serum miR 29c-3p and miR 31-5p in diabetic patients in relation to albuminuria and eGFR. Also, the correlations between these miRNAs and cystatin C were assessed. This study was … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 1 · 17 Feb 2022 · 6,456 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence and Mathematical Modelling-Based Techniques to Improve Social Media MarketingKiran Chaudhary, Mohammad Naquibur Rahman, Nabeela Hasan et al.The Businessperson is using social media to do marketing of their product. Almost all people use social media. Most people relate to social media. Social media marketing is beneficial in making the product more popular and easy ways to introduce the product to everyone in economical ways. In this study, we introduce the concept of machine learning and mathematical models … …Journal of Computer Science, Vol. 21, Issue 1 · 5 Dec 2024 · 5,486 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing N-linked Glycosylation Site Prediction in Human Proteins with Ensemble Stacking and Cross-ValidationMubina Malik, Jaimin UndaviaThe most frequent post-translational modification of proteins in all territories is glycosylation which impacts many biological activities. The most significant and critical of these modifications is N-linked glycosylation which is associated with various human diseases including diabetes cancer Inflammation Alzheimers and atherosclerosis. This article illustrates recent advances in knowledge of biology that are eventually targeting the computer science sector. Moreover-identification … …Journal of Computer Science, Vol. 20, Issue 12 · 20 Nov 2024 · 5,005 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing IoT RPL Protocol Security Against Black Hole Attacks with Deep Learning TechniquesKrari Ayoub, Hajami Abdelmajid, Toubi Ayoub, Mihi SoukainaAs the Internet of Things (IoT) extends its reach into critical infrastructures, it encounters escalating security threats, particularly black hole attacks that jeopardize network communication. The growing use of IoT in essential services underscores the need for robust network integrity. Driven by this urgency, our research has developed a sophisticated detection framework that effectively identifies black hole attacks within IoT … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Oct 2024 · 5,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractCorrelation of Some Tumor Markers Between Serum and Saliva of Patients with Breast CancerHuthaifa Tarawneh, Omar AtroozBreast cancer, which affects 36% of all female oncological patients, is the most frequent cancer in the world among women. Since routine laboratory evaluation of serum can be stressful for patients, it is critical to comprehend the features and limitations of salivary test methods in order to achieve an accurate diagnosis of breast cancer. The purpose of the study is … …OnLine Journal of Biological Sciences, Vol. 25, Issue 1 · 12 Oct 2024 · 4,909 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Garbage Classification Using Balanced and Unbalanced Dataset with EfficientNetV2B1 ArchitectureRetinderdeep Singh, Chander Prabha, Ayman Noor et al.This research concentrates on EfficientNetV2B1 deep learning model to classify garbage collection tasks, with both balanced and unbalanced dataset configurations. The dataset includes 7,260 images for the balanced dataset and 15,515 for the unbalanced one, both of the datasets are used to train and evaluate the model. Training and evaluation of the deep learning model with the standard performance variables: … …Journal of Computer Science, Vol. 20, Issue 10 · 27 Aug 2024 · 5,096 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrognosis of Dementia Using Early Fusion Approach with Digital Clock Drawing and Trail-Making TestsShridevi Karande, Vrushali KulkarniDementia poses a substantial global public health challenge. Emerging evidence suggests that COVID-19's neurological impact may aggravate dementia incidences. Timely recognition and management can significantly decelerate dementia progression and enhance affected individuals' quality of life. In the realm of cognitive assessment, the Clock Drawing Test (CDT) and Trail-Making Test (TMT) stand as prominent tools. Existing research predominantly focuses on the … …Journal of Computer Science, Vol. 20, Issue 8 · 10 Jun 2024 · 4,730 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Smartphone Addiction in Teenagers: An Integrative Model Incorporating Machine Learning and Big Five Personality TraitsJacobo Osorio, Marko Figueroa, Lenis WongSmartphone addiction has emerged as a growing concern in society, particularly among teenagers, due to its potential negative impact on physical, emotional social well-being. The excessive use of smartphones has consistently shown associations with negative outcomes, highlighting a strong dependence on these devices, which often leads to detrimental effects on mental health, including heightened levels of anxiety, distress, stress depression. … …Journal of Computer Science, Vol. 20, Issue 2 · 29 Dec 2023 · 8,238 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,195 accessesView PDFCite