Data Modeling
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Data Modeling
Data Modeling is an international, open access, peer-reviewed journal dedicated to the publication of high-quality research in mathematical, computational, and data-driven modeling across diverse scientific domains. The jour
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Data Modeling
Volume 7 Number 1 2026
Table of Contents
Research Article
Biomedical Data Modeling
Akib Ullah Jafor 1*, Pronati Das Puja 2, Shawanti Biswas 3, Arko Saha 4, Kamruzzaman Mithu 1, Khondaker Abdullah-Al-Mamun 1
Machine learning–driven CGM analysis enables early, personalized prediction of gestational diabetes glycemic patterns, improving maternal-fetal outcomes and clinical decision support.
Abstract | Full Text | Open Access Article
The peer-reviewed and edited version of record published online before inclusion in an issue
These articles have been peer reviewed and accepted for publication. They are still in production and have not been edited, so may differ from the final published form.
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Interpretable Machine Learning Data Modeling for Liver Disease Risk Profiling: Insights from the Indian Liver Patient Dataset
This study bridges predictive modeling and clinical interpretability, enabling transparent, individualized liver disease risk assessment to support more informed, human-centered healthcare decisions.
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HCNN-LSTM with BERT Embeddings and TomekLinks for Imbalanced News Text Classification
This study presents a robust hybrid framework that improves imbalanced news classification through contextual embeddings, better minority-class recognition, and superior performance.
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Early Prediction of Postprandial Glycemic Response in Gestational Diabetes Using Continuous Glucose Monitoring and Gradient Boosting Models
Machine learning–driven CGM analysis enables early, personalized prediction of gestational diabetes glycemic patterns, improving maternal-fetal outcomes and clinical decision support.