Research ArticleOpen accessIn the abstractEvaluation of an Intelligent Electronic Prescription Ontology Using Open Source Tools: A Botswana Case StudyTshiamo Sigwele, Eunice Okon, Tshepiso Mokgetse, Onkemetse TshenyegoHealthcare interoperability in Botswana is hindered by fragmented information exchange across public and private providers, resulting in prescription conflicts, duplicated treatment, and delayed care. In prior work, we developed the Intelligent Electronic Prescription Ontology (IEPO), an open-source OWL 2 ontology for semantically standardized prescription data exchange. Although IEPO was previously validated using competency question-driven metrics (recall, precision, and F1-score), those … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 513 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnsemble Feature Selection for Elderly Health Condition ClassificationRattanawadee PanthongFeature selection is a pivotal technique for constructing classification models with high-dimensional data. It facilitates the identification and elimination of redundant or irrelevant features, thereby reducing model complexity and enhancing predictive accuracy. The success of a classification model largely depends on the quality of the selected features. Accordingly, feature selection is performed during data preparation, prior to data processing, to … …Journal of Computer Science, Vol. 22, Issue 8 · 31 Aug 2026 · 782 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 933 accessesView PDFCite
Research ArticleOpen accessIn the abstractImpact of Integrated Nursing and Digital Droplet PCR on Bullous Dermatoid Conditions: A Randomized Controlled TrialConghui ChenBullous skin disease is an autoimmune disease characterized by the formation of blisters on the skin or mucous membrane, which seriously impairs the quality of life and overall health. Similar to the research on biomolecules (mechanics of protein interaction), cells (including cell membrane elasticity, cell adhesion, cytoskeletal dynamics, response to mechanical stimulation, cell deformation and cell endoforce transfer) and tissue … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 2 Jul 2026 · 993 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,318 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,043 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Neural Network-Based Approach to Sickle Cell Disease-Related Pain ClassificationZacchaeus Omogbadegun, Israel Ogundele, Olufunke OladipupoSickle Cell Disease (SCD), an inherited Red Blood Cell (RBC) disorder, is characterized by anaemia, end-organ damage, unpredictable episodes of pain and early mortality. SCD affects 25% of people living in Central and West Africa causing life threatening “silent” strokes and lifelong damage. Nigeria accounts for 50% of SCD births worldwide (estimated 150,000 of 300,000 babies born with Symptomatic Sickle … …Journal of Computer Science, Vol. 15, Issue 6 · 28 Jun 2019 · 7,683 accessesView PDFCite