Research ArticleOpen accessIn the abstractCA-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 abstractImproved Intrusion Detection System to Alleviate Attacks on DNS ServiceHani Mahmoud Al-Mimi, Nesreen Adnan Hamad, Mosleh Mohammad Abualhaj et al.Cybercriminals continuously devise new and more sophisticated ways to attack their targets’ security and cyberattacks are on the rise. One of the earliest and most vulnerable network services is the Domain Name System (DNS), which has had several security issues that have been repeatedly exploited over time. Building a strong Intrusion Detection System (IDS) that guards against unwanted access to … …Journal of Computer Science, Vol. 19, Issue 12 · 9 Nov 2023 · 5,786 accessesView PDFCite
Research ArticleOpen accessIn the abstractProcess Approach-Based Simulation Project Life Cycle: PAB-SPLCKhadija Ouazzani-Touhami, Kawtar Tikito, Nissrine SouissiSimulation is one of the most effective decision support tools available to designers and managers of complex systems. In particular, discrete-event simulation is widely used in a wide variety of fields, such as industry and production, finance and economics, or even health and services. In addition, the conduct of a simulation project is of extreme importance, in order to carry … …Journal of Computer Science, Vol. 19, Issue 8 · 15 Jul 2023 · 5,398 accessesView PDFCite
Research ArticleOpen accessIn the abstractBreast Cancer Grading using Machine Learning Approach AlgorithmsHiba Nabeel Zalloum, Saada Al Zeer, Amir Manassra et al.Recently, Breast Cancer (BC) becomes a more common cancer disease in women and it considers the most important sign which leads to death among women. Therefore, it requires efficient methods for detecting it to reduce the risk of death. A positive prognosis and greater chances of survival are improved if the BC is detected early. Currently, machine learning plays an … …Journal of Computer Science, Vol. 18, Issue 12 · 22 Dec 2022 · 6,610 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassify Breast Cancer Patients using Hybrid Data-Mining TechniquesFaris E. Mohammed, Nadia Smaoui Zghal, Dalinda Ben Aissa, Mostafa Mahmoud El-GayarAccording to the World Health Organization (WHO), breast cancer is a disease that leads to death, especially for women who have neglected or ignored the risk factors. Doctors can classify patients according to clinical information, famous disease symptoms, or similar cases. But, some cases are difficult to detect early or diagnose accurately. Therefore, the most important challenge faced by researchers … …Journal of Computer Science, Vol. 18, Issue 4 · 12 May 2022 · 6,526 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 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 abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractIrrigation System Using Hyperspectral Data and Machnie Learning Techniques for Smart AgricultureSanthi Balachandran, Sourna Lakshmi, Nithya RajendranWater is the main resource for agriculture. Management of water in agricultural field is a challenging process. To manage the water content in the agricultural field, smart irrigation system has been proposed by using fuzzy based decision support system on Hyperspectral Image benchmark dataset. Hyperspectral images are the process of collected and processed the images from electromagnetic spectrum. Recent studies … …Journal of Computer Science, Vol. 16, Issue 4 · 15 Apr 2020 · 7,683 accessesView PDFCite