Optimized model prediction performance. by Guang Tu (22054865)

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

Comparison statistics of different machine learning algorithms including MLP, GRNN, and RBF for modeling and predicting callogenesis rate and callus fresh weight of petunia. by Hamed Rezaei (11085366)

Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models by Ping Hou (17213)

“…In this study, artificial neural network models are developed to predict chemical ecotoxicity (HC₅₀) based on experimental data to fill data gaps in a widely used database (USEtox). …”

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. by Danish M. Anwer (15383441)

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

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

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

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Data-Driven Development of Heterogeneous Catalysts for Propane Dehydrogenation with Machine Learning and Metaheuristic Optimization by 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 by 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). …”

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

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

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Correlation plot of matrix C_<i>b</i> that includes the estimated within-model and cross-model correlations of personal effects. by Jari Turkia (17912475)

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Predictive model-building process. by Mukhtar Ijaiya (18935122)

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

Comparison of models performance metrics. by Mukhtar Ijaiya (18935122)

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

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

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

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

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Community modeling. by Colton J. Lloyd (5484473)

A schematic view of the step-by-step computational approach in the current study. by Hamed Rezaei (11085366)