Research ArticleOpen accessIn the keywordsIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 accessesView PDFCite
Review ArticleOpen accessIn the keywordsMachine Learning Advancements for Lung Cancer Detection: An In-Depth Review and Future ProspectsAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarLung cancer is a major cause of cancer-related mortality globally, underscoring the necessity for efficient diagnostic instruments. The review paper summarizes the role of ML and DL in detection, staging, and prognostication of lung cancer. We evaluate the relative efficacy of several models, such as CNNs, SVMs, and ensemble approaches, by analyzing publically accessible imaging and molecular information. We emphasize … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Mar 2026 · 1,794 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCA-LIME: A Collinearity-Aware LIME Framework for Reliable and Interpretable Explanations in Healthcare AIIdris Khan, Sachin BhoiteIn clinical tabular models, correlated biomarkers can make local explanations unstable even when predictive performance appears acceptable. This paper presents CA-LIME, a collinearity-aware extension of LIME built to address that failure mode directly. Five variations of CA-LIME Vanilla reference, VIF, PCA back projection, Ridge, and ElasticNet allow us to investigate how various correlation-control strategies alter explanation behavior. ILPD, Kaggle liver, … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 806 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Metaheuristic-Optimized Feature Selection for Early-Stage Diabetes Prediction With SHAP-Guided Insight into Influential AttributesEsmay Azam Rochy, Jannatul Ferdaus, Uzzal Biswas et al.Diabetes is a metabolic disorder that causes elevated blood glucose. This long-term health condition can lead to cardiovascular diseases, stroke, kidney failure, visual impairment, neuropathy, and even death in critical cases. So, a Computer-Aided Diagnostic (CAD) system is necessary to diagnose diabetes automatically. A clinician can utilize a machine learning-based CAD system that automatically diagnoses many people. This paper will … …Journal of Computer Science, Vol. 22, Issue 2 · 24 Feb 2026 · 1,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 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 · 2,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence in Quality Control: Transforming Manufacturing ProcessesGopinath KathiresanThe integration of Artificial Intelligence (AI) into Quality Control (QC) is transforming manufacturing by enhancing accuracy, efficiency, and productivity. Traditional QC methods, reliant on manual inspection and basic automation, often fall short in addressing the complexities of modern production environments. This paper presents a review on the application of AI, particularly machine learning, deep learning, and reinforcement learning, in manufacturing … …Journal of Computer Science, Vol. 22, Issue 1 · 12 Feb 2026 · 6,492 accessesView PDFCite