Fig 5 - by Maryam Shadi (14237349)

Fig 11 - by Maryam Shadi (14237349)

Fig 3 - by Maryam Shadi (14237349)

Image_3_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Patients... by Mingxue Yu (10273496)

Image_4_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Patients... by Mingxue Yu (10273496)

Image_5_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Patients... by Mingxue Yu (10273496)

Image_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 Patients... by Mingxue Yu (10273496)

Image_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 Patients... by Mingxue Yu (10273496)

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)

Comparison of the four models. by Gaosha Li (20570760)

“…Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis.…”

Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx by Xinping Lin (1591438)

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

Supplementary file 1_Machine learning algorithms to predict epidural-related maternal fever: a retrospective study.docx by Xiaohui Guo (131711)

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

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. …”

Set of variables VS model performance. by Gaosha Li (20570760)

“…Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis.…”

Data_Sheet_1_Early detection of sepsis using machine learning algorithms: a systematic review and network meta-analysis.pdf by Mikhail Ya Yadgarov (18543769)

Supplementary file 1_Development of a venous thromboembolism risk prediction model for patients with primary membranous nephropathy based on machine learning.docx by Lian Li (49049)

“…Objective<p>This study utilizes real-world data from primary membranous nephropathy (PMN) patients to preliminarily develop a venous thromboembolism (VTE) risk prediction model with machine learning. …”

Data_Sheet_1_Phase-wise evaluation and optimization of non-pharmaceutical interventions to contain the COVID-19 pandemic in the U.S..pdf by Xiao Zhou (122661)

“…We further assess the effectiveness of existing COVID-19 control measures and explore potential optimal strategies that strike a balance between public health and socio-economic recovery for individual states in the U.S. by employing the Pareto optimality and genetic algorithms. …”

DataSheet_1_Stronger wind, smaller tree: Testing tree growth plasticity through a modeling approach.docx by Haoyu Wang (429641)

“…The result shows that the challenging task of modeling plant plasticity may be solved by optimizing the plant fitness function. …”