Path analysis diagram illustrating the associations between alexithymia, social support, anticipated stigma and patient satisfaction, with their respective correlation coefficients... حسب Keya Bibikar (22386306)

Comparison of the results of our model and other methods. حسب Weijia Zhu (65481)

Fig 6 - حسب Samuel Hylander (331771)

Out-of-sample Test Results of the Drop-off Decision Models: (a) ROC Curve of the First Forced Drop-off Decision Models; (b) ROC Curve for Second and More Forced Parking and Drop-of... حسب Fangyi Yang (18867853)

الموضوعات:

P values of Kruskal–Wallis test at 95% significance level. حسب Fahd Saeed Alakbari (10701871)

الموضوعات:

Synthetic feasibility scores of 20 molecular fragments. حسب Bin Pan (742525)

الموضوعات:

The scatter plot of the target variable solubility dataset. حسب Bin Pan (742525)

الموضوعات:

Samples with the highest solubility after high-throughput screening. حسب Bin Pan (742525)

الموضوعات:

Assessment values of machine learning models. حسب Bin Pan (742525)

الموضوعات:

List of datasets in AqSolDB. حسب Bin Pan (742525)

الموضوعات:

Schematic workflow diagram of the StackBoost model framework. حسب Bin Pan (742525)

الموضوعات:

Comparison of training and predicted values of compound water solubility for different machine learning models: (A) AdaBoost, (B) GBDT, (C) LGBM, (D) RF, (E) XGBoost, (F) RF, and (... حسب Bin Pan (742525)

الموضوعات:

Pearson correlation analysis between pairs of feature parameters. حسب Bin Pan (742525)

الموضوعات:

Comparison of actual vs predicted values after transfer. حسب Bin Pan (742525)

الموضوعات:

List of available information in each column of AqSolDB. حسب Bin Pan (742525)

الموضوعات:

3D Scatter plot of features related to water-soluble materials. حسب Bin Pan (742525)

الموضوعات:

Workflow diagram of the prediction algorithm framework. حسب Bin Pan (742525)

الموضوعات:

Feature importance derived from SHAP analysis. حسب Bin Pan (742525)

الموضوعات:

Results of longitudinal analysis of mental health in HCWs. حسب A. H. Ayesha Lavell (16734002)

Comparison of Model Five-classification Results. حسب Chao Tang (10925)

"…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …"