ROC curves for the test set of four models. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging حسب D. Andrew Brown (6584837)

SHAP bar plot. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

Sample screening flowchart. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

Descriptive statistics for variables. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

SHAP summary plot. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

Display of the web prediction interface. حسب Meng Cao (105914)

"…According to the SHAP analysis of the optimal model, the most influential predictors are age, education level, and hemoglobin concentration.…"

The data processing and analysis pipeline. حسب Xin Zhang (35492)

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx حسب Yuhong Huang (115702)

"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"

Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP حسب Xiaofeng Wang (119575)

Data_Sheet_1_The impact of family urban integration on migrant worker mental health in China.docx حسب Xiaotong Sun (6535064)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx حسب Çaǧlar Çaǧlayan (12253934)

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach حسب Sanaa Badr (20628838)

"…Binary classification models were developed to classify cases into two groups: those transferring two or fewer embryos and those transferring three or four. …"

Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx حسب Ali Nabavi (21097424)

"…., blood lead and cadmium levels) were analyzed as features, with hearing loss status—defined as a pure-tone average threshold exceeding 25 dB HL across 500, 1,000, 2000, and 4,000 Hz in the better ear—serving as the binary outcome. Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …"