AUROC Graphs of RF Model and ResNet. 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. …"

PCA-CGAN Model Workflow Diagram. 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. …"

Structural Diagrams of RF Model and ResNet Model. 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. …"

PCA-CGAN model convergence curve. 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. …"

PCA-CGAN Structure Diagram. 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. …"

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. …"

PCAECG-GAN K-fold experiment table. 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. …"

PCA-CGAN Pseudocode Table. 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. …"

PCA-CGAN Ablation Experiment 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. …"

Antibody description. حسب Qi He (384033)

"…It was observed led to a regulation in the expression of mitochondrial quality control proteins, consequently improving mitochondrial biogenesis (Nrf1, PGC-1α, Tfam), and increasing ATP production. Furthermore, HRW decreased Cytc, Bax, Caspase-3, and Caspase-8 levels, and increasing the expression of Bcl-2. …"

Raw data of this article. حسب Qi He (384033)

"…It was observed led to a regulation in the expression of mitochondrial quality control proteins, consequently improving mitochondrial biogenesis (Nrf1, PGC-1α, Tfam), and increasing ATP production. Furthermore, HRW decreased Cytc, Bax, Caspase-3, and Caspase-8 levels, and increasing the expression of Bcl-2. …"

Model fit indices for social isolation. حسب Juhee Choi (2619733)

"…Since the onset of the pandemic, the prevalence of depression and anxiety has significantly increased. Quarantine and social distancing, implemented to control the spread of COVID-19, have exacerbated social isolation. …"

Multilevel model analysis of social isolation. حسب Juhee Choi (2619733)

"…Since the onset of the pandemic, the prevalence of depression and anxiety has significantly increased. Quarantine and social distancing, implemented to control the spread of COVID-19, have exacerbated social isolation. …"

PCAIs inhibit NCI-H23 cell line viability. حسب Matthew D. Gregory (19929096)

"…However, CRAF/RAF1 phosphorylation decreased by 40%, suggesting significant changes in the KRAS/MAPK signaling patterns. …"

PCAIs disrupt actin filaments in NCI-H23 cells. حسب Matthew D. Gregory (19929096)

"…However, CRAF/RAF1 phosphorylation decreased by 40%, suggesting significant changes in the KRAS/MAPK signaling patterns. …"

PCAIs suppress 3D NCI-H23 cell invasion. حسب Matthew D. Gregory (19929096)

"…However, CRAF/RAF1 phosphorylation decreased by 40%, suggesting significant changes in the KRAS/MAPK signaling patterns. …"

PCAIs suppress NCI-H23 cancer cell migration. حسب Matthew D. Gregory (19929096)

"…However, CRAF/RAF1 phosphorylation decreased by 40%, suggesting significant changes in the KRAS/MAPK signaling patterns. …"

PCAIs induce apoptosis in NCI-H23 cells. حسب Matthew D. Gregory (19929096)

"…However, CRAF/RAF1 phosphorylation decreased by 40%, suggesting significant changes in the KRAS/MAPK signaling patterns. …"

Contents of PIO Program. حسب Jun-Seo Lim (21161776)

"…The difference between the two groups was statistically significant (<i>t</i> = 3.94, <i>p</i><.001). Depression decreased -0.7±3.48 in the experimental group, from 5.9±4.74 before intervention to 5.2±4.65 after intervention, and decreased by -0.2±3.42, from 6.5±4.69 before intervention to 6.4±4.08 after intervention, in the control group, but the difference between the two groups was not statistically significant (<i>z</i> = -0.59, <i>p</i> =.557). …"

Demographic characteristics of participants. حسب Jun-Seo Lim (21161776)

"…The difference between the two groups was statistically significant (<i>t</i> = 3.94, <i>p</i><.001). Depression decreased -0.7±3.48 in the experimental group, from 5.9±4.74 before intervention to 5.2±4.65 after intervention, and decreased by -0.2±3.42, from 6.5±4.69 before intervention to 6.4±4.08 after intervention, in the control group, but the difference between the two groups was not statistically significant (<i>z</i> = -0.59, <i>p</i> =.557). …"