Algorithms and evaluation metrics integrated in the COPS framework. by Teemu J. Rintala (19333003)

Data Sheet 1_TBESO-BP: an improved regression model for predicting subclinical mastitis.pdf by Kexin Han (10933209)

“…The model is based on TBESO (Multi-strategy Boosted Snake Optimizer) and utilizes monthly Dairy Herd Improvement (DHI) data to forecast the status of subclinical mastitis in cows.…”

Data_Sheet_1_Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence.PDF by Vito Janko (14605643)

Image_1_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

Image_2_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

Data_Sheet_1_A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions.PDF by Leon Lufkin (11276856)

Data used in this study. by Qinghua Li (398885)

“…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx by Liyin Zhang (6371999)

Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation. by Aly A. Valliani (13251484)

“…<p><b>(A)</b> There are four primary methods by which machine learning models can be deployed in a context with distinct data domains: 1) train a model on one domain and deploy it across multiple distinct domains, 2) train multiple bespoke models that are optimized for deployment on individual domains, 3) train and deploy a single global model on all domains, and 4) train a model on one domain and adapt it through technical means to make it performant on a distinct domain. …”

Data_Sheet_1_Determination of phage load and administration time in simulated occurrences of antibacterial treatments.docx by Steffen Plunder (14022498)

Data_Sheet_1_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Pat... by Mingxue Yu (10273496)

Data_Sheet_2_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Pat... by Mingxue Yu (10273496)

DEM error verified by airborne data. by Qinghua Li (398885)

“…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”

A portfolio selection model based on the knapsack problem under uncertainty by Fereshteh Vaezi (6655028)

“…The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. …”

S1 Data - by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change" by Ziyu Lin (9151064)

Iteration curve of the optimization process. by Meijun Shang (22806461)

“…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …”

Error of ICESat-2 with respect to airborne data. by Qinghua Li (398885)

“…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”

Table_1_Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation.docx by Jiajin He (13386702)

The prediction error of each model. by Hao Yang (328526)

“…The model is developed and validated using data from 159 debris flow-prone gullies, integrating deep convolutional, recurrent, and attention-based architectures, with hyperparameters autonomously optimized by IKOA. …”