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84 results for “Predictive Analysis”
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Research ArticleOpen accessIn the abstractMMP-9 is a Potential Prognostic Marker of Left Ventricular Remodeling in Patients with Coronary Artery DiseaseMikhail Aleksandrovich Popov, Anastasia Vladimirovna Poznyak, Dmitry Valerievich Shumakov et al.Matrix Metalloproteinase-9 (MMP-9) emerges as a promising prognostic marker for assessing left ventricular remodeling in patients with coronary artery disease, particularly in the context of Ischemic Heart Disease (IHD) complicated by left ventricular aneurysm. In this study, we conducted two parallel investigations to explore the prognostic significance of MMP-9 in patients with multivessel coronary artery disease undergoing left ventricular reconstruction … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 11 Jul 2024 · 4,310 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 481 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite
Research ArticleOpen accessIn the abstractFrom Digital Engagement to Social Welfare: Measuring the Impact of the mSmart Application in a Developing RegionHendro Nindito, Evaristus Didik Madyatmadja, Siti Elda Hierra, MaryaniThe mSmart platform, introduced as a pilot initiative in Labuan Bajo, Indonesia, was developed to strengthen community participation in local digital services. This study explores the extent to which the application delivers social value to its users and the broader community. Guided by the Information Systems Success Model (ISSM) and the WebQual framework, the research focuses on three main factors: … …Journal of Computer Science, Vol. 22, Issue 5 · 25 May 2026 · 1,228 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Review ArticleOpen accessIn the abstractAdopting Artificial Intelligence in ERP Systems as an Innovation to Support Business Growth: A Systematic Literature ReviewAmalia Sulfinita Lawendatu, Fajar Hidayat, Fathy Radhia, Sugiarto HartonoDigital transformation is driving the integration of Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems as an innovative strategy to improve organizational competitiveness. However, consolidated knowledge regarding the benefits and challenges of this integration remains scarce. This study utilizes a Systematic Literature Review (SLR) in accordance with the PRISMA framework to analyze 31 peer-reviewed articles published between 2020 and … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,105 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecoding Lung Cancer: PLAU as a Critical Driver and Diagnostic MarkerStanley Cho, Min Gyeong KimLung cancer remains a leading cause of cancer-related mortality, and understanding its underlying molecular mechanisms is critical for developing targeted therapies. We developed a novel tool called the Transcriptome-TCGA Integration (TTI), which combines in vitro transcriptome data with clinical datasets from the Cancer Genome Atlas (TCGA). TTI allows for the identification of key genes and pathways involved in lung cancer, … …OnLine Journal of Biological Sciences, Vol. 25, Issue 4 · 15 Feb 2026 · 1,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Virtual Modeling Approach for Mango Tree Biomass Estimation Using Allometric Equations and Functional-Structural Plant Modeling (FSPM) with GroIMPOki Marzuqi, Ditdit Nugeraha Utama, Azhar Indra RusmanaBiomass represents a critical ecological contribution of trees, including mango (Mangifera indica L.), necessitating rigorous academic approaches for quantification and modeling. This study develops a computational model to enhance understanding of mango tree morphology and physiology using Functional-Structural Plant Modeling (FSPM) implemented through GroIMP software. Comparative analysis reveals that the FSPM-based biomass model generates higher estimates than traditional allometric equations, … …Journal of Computer Science, Vol. 21, Issue 11 · 12 Feb 2026 · 1,282 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine-Tuned and Optimized Transformer-Based Model for EEG Seizure DetectionPuspanjali Mallik, Ajit Kumar Nayak, Kumar Janardan Patra et al.Epilepsy, a widely recognized neurological disorder, results from irregularities in the transmission of electrical impulses among neurons in the brain. Over the last two decades, significant efforts have been made by researchers and clinicians to develop effective methods for its early detection and management. The electroencephalogram (EEG), a non-invasive tool used to monitor brainwave activity, has become a central device … …Journal of Computer Science, Vol. 21, Issue 11 · 11 Feb 2026 · 1,412 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite