Developing a nomogram for predicting depression in diabetic patients after COVID-19 using machine learning by Haewon Byeon, Haewon Byeon

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Combined Effects of tDCS and Language/Cognitive Intervention on the Naming of Dementia Patients: A Systematic Review and Meta-Analysis by Haewon BYEON

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Predicting High-Risk Groups for COVID-19 Anxiety Using AdaBoost and Nomogram: Findings from Nationwide Survey in South Korea by Haewon Byeon

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Beyond the Usual Suspects: A Genetic Perspective on Toxoplasmosis-Related Recurrent Abortion and IL-18 by Haewon Byeon

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Influence of the COVID-19 Pandemic on the Subjective Life Satisfaction of South Korean Adults: Bayesian Nomogram Approach by Haewon Byeon

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The association between lifetime cigarette smoking and dysphonia in the Korean general population: findings from a national survey by Haewon Byeon

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Determinants of blood pressure control in hypertensive individuals using histogram-based gradient boosting: findings from 1114 male workers in South Korea by Haewon Byeon

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Empowering energy with a cutting-edge reversible logic framework for universal shift registers by Haewon Byeon

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Comparing Ensemble-Based Machine Learning Classifiers Developed for Distinguishing Hypokinetic Dysarthria from Presbyphonia by Haewon Byeon

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Association among smoking, depression, and anxiety: findings from a representative sample of Korean adolescents by Haewon Byeon

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Predicting occupational musculoskeletal disorders in South Korean male office workers using a robust and sparse twin support vector machine by Haewon Byeon

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Exploring the novel environmentally friendly highly hydrophobic TiO2 coating for enhanced anti-corrosion performance of steel in potential industrial applications by Haewon Byeon, J. Sunil

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Searching for Optimal Oversampling to Process Imbalanced Data: Generative Adversarial Networks and Synthetic Minority Over-Sampling Technique by Gayeong Eom, Haewon Byeon

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Explainable Deep-Learning-Based Depression Modeling of Elderly Community after COVID-19 Pandemic by Hung Viet Nguyen, Haewon Byeon

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Prediction of ECOG Performance Status of Lung Cancer Patients Using LIME-Based Machine Learning by Hung Viet Nguyen, Haewon Byeon

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YOLOv7-based automated detection platform for scalp lesions by Hung Viet Nguyen, Haewon Byeon

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A hybrid self-supervised model predicting life satisfaction in South Korea by Hung Viet Nguyen, Haewon Byeon

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Predicting dementia in Parkinson's disease on a small tabular dataset using hybrid LightGBM–TabPFN and SHAP by Vinh Quang Tran, Haewon Byeon

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LIME-based ensemble machine for predicting performance status of patients with liver cancer by Hung Viet Nguyen, Haewon Byeon

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Predicting Depression during the COVID-19 Pandemic Using Interpretable TabNet: A Case Study in South Korea by Hung Viet Nguyen, Haewon Byeon

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