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binary data » primary data (Expand Search), dietary data (Expand Search)
binary risk » primary risk (Expand Search), dietary risk (Expand Search)
data joint » data point (Expand Search), data points (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
risk learning » task learning (Expand Search), xlink learning (Expand Search), cross learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary risk » primary risk (Expand Search), dietary risk (Expand Search)
data joint » data point (Expand Search), data points (Expand Search)
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
Published 2022“…Introduction: Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. …”
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Table 1_Creating an interactive database for nasopharyngeal carcinoma management: applying machine learning to evaluate metastasis and survival.docx
Published 2024“…This study aims to develop and apply machine learning models to predict DM, overall survival (OS), and cancer-specific survival (CSS) in NPC patients to provide optimal tools for improved predictive accuracy and performance.…”
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Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png
Published 2025“…</p>Results and Discussion<p>Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. …”
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Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
Published 2022“…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…Both the SVM model with a linear kernel and the one with an RBF kernel achieved identical results. Optimization with GridSearchCV corroborated this stagnation, identifying a simple linear model (C=0.05, gamma='scale') as the optimal configuration, indicating that the additional complexity of nonlinear kernels did not confer predictive gains. …”