Research ArticleOpen accessIn the keywordsA Distribution-Free Bayesian Approach for Indirect ComparisonsJohanna S. van Zyl, Jack D. TubbsThe objective of this paper is to consider an indirect comparison between treatments B and C when each have been compared directly to treatment A in separate studies. Problems of this type are common in Network Meta-Analysis (NMA). A commonly used method assumes that the underlying data, Y, are normally distributed and µ = E(Y) is the measure of clinical … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 3 Jul 2019 · 6,687 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 abstractApplication of Machine Learning for the Detection of Depression and Mindfulness as a Mitigation MethodSantiago Domingo Moquillaza Henriquez, Liliana Ruth Huamán Rondón et al.Depression is a global mental health problem with various causes. Nowadays, with Artificial Intelligence, it can be predicted in order to take preventive measures, whether at a psychotherapeutic or pharmacological level. This research, based on a survey conducted, detects depression using logistic regression with a 91% fit to the ROC-AUC model, accuracy of 0.839188, precision 0.851354. In addition, a study … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,216 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 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
Research ArticleOpen accessIn the abstractArtificial Intelligence and Mathematical Modelling-Based Techniques to Improve Social Media MarketingKiran Chaudhary, Mohammad Naquibur Rahman, Nabeela Hasan et al.The Businessperson is using social media to do marketing of their product. Almost all people use social media. Most people relate to social media. Social media marketing is beneficial in making the product more popular and easy ways to introduce the product to everyone in economical ways. In this study, we introduce the concept of machine learning and mathematical models … …Journal of Computer Science, Vol. 21, Issue 1 · 5 Dec 2024 · 5,478 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of a Beta Regression Model for Covariate Adjusted ROCXing Meng, J.D. TubbsThe Receiver Operating Characteristic (ROC) curve and the area under the ROC (AUC) are widely used in determining the diagnostic capability of a binary classification procedure. Since the test performance is affected by covariates, the ROC and AUC have been utilized in a Generalized Linear Regression (GLM) setting. In this study, we revisit a problem where the AUC regression model … …Current Research in Biostatistics, Vol. 10, Issue 1 · 18 Jun 2020 · 13,966 accessesView PDFCite