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68 results for “Intervention model”
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Research ArticleOpen accessIn the abstractDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptiCNN: Local thresholding segmentation and CNN with SVM Approach for Diabetic Retinopathy Detection and Classification of Fundus ImagesAnju Mishra, Mrinal Pandey, Laxman SinghDiabetic Retinopathy (DR) is a progressive eye disease that can lead to vision loss and blindness if left untreated. Ophthalmologists diagnose DR using medical imaging modalities such as fundus photography and optical coherence tomography (OCT); however, manual interpretation of these images is time-consuming and subject to inter-observer variability. While DR is irreversible, vision loss can be prevented through early detection … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,153 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractFactors Associated with Irrational Use of Antibiotics. A Cross-Sectional Study in the City of Marrakech MoroccoNaima Aoutil, Mohamed Cherkaoui, Mohamed BouskraouiOveruse and inappropriate use of antibioticsleads to the emergence of antibiotic-resistant bacteria. This resistance leadsto longer hospital stays, higher medical costs, and increased mortality. Therefore,its control must be a priority as it poses a threat to all nations, regardlessof their territory and economic status.In Marrakech too, antibioticresistance is a real public health problem, limiting treatment options. Thepopulation plays a crucial … …OnLine Journal of Biological Sciences, Vol. 25, Issue 1 · 6 Feb 2025 · 4,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractProposed Self-Regulation Model for Collaborative E-Learning Systems in Kenyan Public UniversitiesGrace Leah Akinyi, Robert ObokoIntegration of technology in learning such as Electronic-learning has become an indispensable segment of higher education in Sub-Saharan Africa. This has opened up opportunities that improve teaching and learning. There is need for intervening in e-learning environments towards developing Self-regulated learning support, which can lead to improvement in performance and learner retention. SRL provides students with capability to acquire and … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 1 · 11 Jan 2020 · 7,717 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffects of Aerobic Exercise on PPAR-γ Expression in Adipose Tissue and RT-PCR Detection AnalysisXiaodong Zhan, Chenguang Bi, Jie WeiThis study aimed to examine the effect of organized aerobic exercise on the expression level of Peroxisome Proliferator-Activated Receptor gamma (PPAR-γ) gene in adipose tissue by performing digital variant of RT-PCR, Droplet Digital PCR (ddPCR) which is a highly sensitive method for counting the gene copy numbers. The proposed scheme consists of three-stage analytical procedure, namely, Subphase I Controlled Aerobic … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 29 Sep 2026 · 580 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Diabetes Risk Prediction Using Ensemble Boosting and SMOTE-Based Class BalancingKittipol Wisaeng, Pankom Sriboonlue, Benchalak MuangmeesriAccurate diabetes prediction is vital for early intervention, optimized resource allocation, and minimizing long-term complications. This study presents a comparative evaluation of traditional and advanced machine learning models for diabetes classification using a structured clinical dataset. Seven baseline algorithms were assessed against five advanced ensemble methods: CatBoost, LightGBM, XGBoost, Voting Ensemble, and Stacking Ensemble. To improve algorithm learning, the Synthetic … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Feb 2026 · 1,976 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractPotential Impacts of Sustainable Dairy Farming in Char Areas of Northern BangladeshJasim Uddin Ahmed, Shankar Kumar Raha, Md. Habibur RahmanThis study was conducted to evaluate the potential impacts of sustainable dairy farming in Char areas of Northern Bangladesh. A total of 600 poorest dairy farming households were selected out of 1323 households, taking 200 households from each Upazila of Sariakandi, Islampur and Belkuchi of Bogra, Jamalpur and Sirajganj districts, respectively using simple random sampling technique. A structured questionnaire was … …American Journal of Agricultural and Biological Sciences, Vol. 12, Issue 3 · 2 Nov 2017 · 8,542 accessesView PDFCite