Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

DataSheet1_Evolutionary algorithm for the optimization of meal intake and insulin administration in patients with type 2 diabetes.PDF حسب Eva Gonzalez-Flo (5046737)

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

"…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …"

Personal details that are used as predictors. حسب Jari Turkia (17912475)

"…The collected data were used to estimate the common hierarchical model, from which personalized models of the patients’ diets and individual reactions were extracted. …"

Nutrient predictors of the model. حسب Jari Turkia (17912475)

"…The collected data were used to estimate the common hierarchical model, from which personalized models of the patients’ diets and individual reactions were extracted. …"

Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

"…Clinical, demographic, and supplement variables were preprocessed into 21 predictors. Four algorithms (K-Nearest Neighbors, Classification and Regression Tree, Support Vector Machine, and Random Forest) were implemented alongside their LR–ABC hybrid counterparts. …"

Schematic representation of semi-automated algorithm for organoids analyzing. حسب Anna Demchenko (18449439)

Data Sheet 5_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 7_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 6_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 3_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 1_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 2_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Data Sheet 4_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf حسب Yuwen ShangGuan (22633190)

"…Dietary data were collected through 24-h dietary recalls, encompassing macronutrients, micronutrients, food processing classification (NOVA), and five dietary quality scores. …"

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

"…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. 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. …"

Latent state estimations for experimental data with no stressors. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with time limit. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with interruptions for subject 18. حسب Samiul Alam (18563323)

Latent state estimations for experimental data with no stressors for subject 22. حسب Samiul Alam (18563323)