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84 results for “Predictive Analysis”
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Research ArticleOpen accessPhrase in the titlePredictive Analysis of BMI and Liver Size on Kidney Function in Young Mexican American PopulationOrlando Patricio, Rohitha Goonatilake, Fernando G. Quintana et al.This study aimed todetermine the probability of fatty liver, hepatomegaly, and liver size ≥2SDwith age in each category of BMI percentile. It also aimed to investigate therelationship between GFR, BMI percentile, liver size, Blood Pressure (BP), andright kidney volume among overweight and obese boys and girls and to identifythe predictors of GFR. 763 records of boys and girls visiting a … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 9 Sep 2022 · 5,540 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Quantitative Analysis of Preparedness and Performance: Predictive Indicators in First-Year Tertiary MathematicsGurudeo Anand TularamStudent preparedness at university entry plays a critical role in determining success in mathematics courses. This study investigates how three observable behaviours: (1) completion of weekly problem sets, (2) regular tutorial attendance, and (3) performance on a mid-semester test. We investigate how they relate to each other and their final examination results. Over five years, data were collected from 450 … …Journal of Social Sciences, Vol. 21, Issue 1 · 10 Oct 2025 · 2,724 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUMPM-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 keywordsAnalyzing Public Sentiment on Demonetization Using SVM: A Machine Learning ApproachKaliappan M, Guruprakash B, Rajalakshmi et al.The Indian economy experienced significant disruption following the implementation of demonetization, a policy initiative aimed at eliminating black money, controlling inflation, and promoting financial inclusion. However, this currency ban generated widespread debate and polarized public opinion. This study analyzes public sentiment toward demonetization using social media data, specifically Twitter posts characterized by mixed sentiments, sarcasm, and nuanced linguistic expressions. We … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,235 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural NetworksShirin A. Mojarad, Satnam S. Dlay, Wai L. Woo, Gajanan V. SherbetProblem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 20 Feb 2012 · 7,699 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUltimate Prediction of Stock Market Price MovementRebwar M. Nabi, Soran Ab. M. Saeed, Habibolah Bin Harron, Hamido FujitaInvestment in the stock market is currently very popular due to its economic gain. Numerous researchers’ and academicians’ work is focused on financial time series prediction due to its data availability and profitability. Therefore, this study presents the design and implementation of a novel binary classification framework to predict stock market trends. The framework is composed of data preprocessing, feature … …Journal of Computer Science, Vol. 15, Issue 12 · 25 Dec 2019 · 8,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultivariate Analysis of Gestational Diabetes Risk Factors in a North African Population: A Call for Targeted Maternal Health InterventionsHafssa Abdellaoui, Nadia Ouzennou, Adnane Hakem, Samia RkhaGestational Diabetes (GD) is a multifactorial condition influenced by demographic, anthropometric and obstetric determinants. Identifying predictive factors is essential to anticipate the disorder, guide prevention strategies and reduce maternal and neonatal complications. To assess the risk factors associated with GDM in pregnant women in the Marrakech-Safi region, in order to fill a gap in national data. A retrospective cross-sectional study … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 10 May 2026 · 1,531 accessesView PDFCite