بدائل البحث:
derived optimization » required optimization (توسيع البحث), design optimization (توسيع البحث), guided optimization (توسيع البحث)
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
its derived » ipsc derived (توسيع البحث), i derived (توسيع البحث), hipsc derived (توسيع البحث)
binary its » binary pairs (توسيع البحث)
derived optimization » required optimization (توسيع البحث), design optimization (توسيع البحث), guided optimization (توسيع البحث)
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), dose optimization (توسيع البحث)
its derived » ipsc derived (توسيع البحث), i derived (توسيع البحث), hipsc derived (توسيع البحث)
binary its » binary pairs (توسيع البحث)
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
منشور في 2022"…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …"
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List of data tables.
منشور في 2025"…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …"
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Flow chart of data source inclusion.
منشور في 2025"…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …"
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Predictive model-building process.
منشور في 2025"…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …"
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Comparison of models performance metrics.
منشور في 2025"…By leveraging ML, HIV programs can implement data-driven, targeted interventions to improve care continuity. …"
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Image 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.jpeg
منشور في 2025"…Predictors included demographics, comorbidities, laboratory parameters, vital signs, and disease severity scores. Missing data (<30%) were imputed using random forest. The cohort was split into training (75%) and internal testing (25%) sets, with hyperparameter optimization via 5-fold cross-validation. …"
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Table 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.docx
منشور في 2025"…Predictors included demographics, comorbidities, laboratory parameters, vital signs, and disease severity scores. Missing data (<30%) were imputed using random forest. The cohort was split into training (75%) and internal testing (25%) sets, with hyperparameter optimization via 5-fold cross-validation. …"
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Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants
منشور في 2019"…Risk prediction models currently recommended by clinical guidelines are typically based on a limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. …"
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