AUROC scores with 95% CI from Day 1 to Day 4 for different algorithms. حسب Armin Abdollahi (21440129)

An example of a key driver diagram to optimize triage rates was developed during the quality improvement process. حسب Rebecca Goertzen (22008461)

Personal algorithmic recommendations of potassium and phosphorous intake and the corresponding concentration predictions. حسب Jari Turkia (17912475)

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Optimized model prediction performance. حسب Guang Tu (22054865)

Data collection during the patients’ usual treatment routine. حسب Jari Turkia (17912475)

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Data-Driven Development of Heterogeneous Catalysts for Propane Dehydrogenation with Machine Learning and Metaheuristic Optimization حسب Jungmok Oh (14117464)

"…This paper presents a hybrid framework that combines ML models with a metaheuristic optimization algorithm, to explore improved heterogeneous catalysts for propane dehydrogenation (PDH). …"

Data-Driven Development of Heterogeneous Catalysts for Propane Dehydrogenation with Machine Learning and Metaheuristic Optimization حسب Jungmok Oh (14117464)

"…This paper presents a hybrid framework that combines ML models with a metaheuristic optimization algorithm, to explore improved heterogeneous catalysts for propane dehydrogenation (PDH). …"

Spatial multivariate optimization for a sampling redesign with a reduced sample size of soil chemical properties حسب Tamara Cantú Maltauro (15199725)

List of data tables. حسب Mukhtar Ijaiya (18935122)

"…Merged demographic, clinic, pharmacy, and laboratory data were included as potential predictor variables in multiple models. …"

Personal recommendations of potassium and phosphorous intake () based on cross-validation predictions of nutrition effects, . Other parameters of the figure are similar to in-sampl... حسب Jari Turkia (17912475)

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Personalized normal ranges for plasma concentrations depending on the age of the patient. حسب Jari Turkia (17912475)

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Intake levels of potassium and phosphorous from the collected food records and their observed effects on these concentrations. حسب Jari Turkia (17912475)

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Correlation plot of matrix C_<i>g</i> that includes the estimated within-model and cross-model correlations in level of dialysis treatment. حسب Jari Turkia (17912475)

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Posterior predictive check (PPC) of the final nutritional effect model. حسب Jari Turkia (17912475)

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Structure of the graphical model with general, treatment, and personal level nutrient effects. حسب Jari Turkia (17912475)

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Comparison of model structures for personal nutrient effects. حسب Jari Turkia (17912475)

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Strongest and personally most varying effects of nutrients and medication. حسب Jari Turkia (17912475)

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Figure shows normalized root mean square error (NRMSE) of the two-level model for each patient. حسب Jari Turkia (17912475)

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

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Effects of potassium and phosphorous between different dialysis treatments and between patients within the same treatment. حسب Jari Turkia (17912475)

الموضوعات: