The patients discharged before the next weekend stratified by day of admission and serum sodium. حسب Rajkumar Rajendram (22505442)

Fig 4 - حسب Maryam Banar (3220221)

Baseline characteristics of the study population. حسب Hanbin Wu (14016246)

"…Compared to the normal group, women with preconception hypoglycemia had increased IPTW-multivariate adjusted ORs of PTB by 10% (95% CI [1.08, 1.12], <i>P</i> < 0.001), LBW by 8% (95% CI [1.03, 1.12], <i>P</i> = 0.001), SGA by 7% (95% CI [1.05, 1.08], <i>P</i> < 0.001), and birth defects by 21% (95% CI [1.06, 1.37], <i>P</i> = 0.004), while the ORs of medical abortion decreased by 6% (95% CI [0.91, 0.98], <i>P</i> = 0.002), miscarriage or early stillbirth by 5% (95% CI [0.92, 0.97], <i>P</i> < 0.001), macrosomia by 12% (95% CI [0.86, 0.90], <i>P</i> < 0.001), and LGA by 12% (95% CI [0.86, 0.89], <i>P</i> < 0.001) if mothers had a preconception hypoglycemia. …"

Stability of Staphylococcus phage vB_SauR_SW21 and Staphylococcus phage vB_SauR_SW25 at various temperatures. حسب Maryam Banar (3220221)

Fig 8 - حسب Maryam Banar (3220221)

Antibody description. حسب Qi He (384033)

"…Western blotting analyzed markers for ferroptosis (GPX4, SLC7A11, HO-1, Nrf2), apoptosis (Bax, Bcl-2, Cytc, Caspase-3, Caspase-8), mitochondrial biogenesis (Nrf1, PGC-1α, Tfam), and quality control (Drp1, Fis1, Mfn1, Mfn2, OPA1, PINK1, Parkin, LC3 I/II).…"

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

"…Western blotting analyzed markers for ferroptosis (GPX4, SLC7A11, HO-1, Nrf2), apoptosis (Bax, Bcl-2, Cytc, Caspase-3, Caspase-8), mitochondrial biogenesis (Nrf1, PGC-1α, Tfam), and quality control (Drp1, Fis1, Mfn1, Mfn2, OPA1, PINK1, Parkin, LC3 I/II).…"

Comparison of the particular blood cell parameters across the various murine treatment groups. حسب Maryam Banar (3220221)

(A) The overexpression of PRDX1 reduces the intracellular ROS level. حسب Jing Chen (4762)

"…After overexpression of chIRAP, the intensity of red fluorescence in mitochondria decreased significantly, while the green fluorescence increased significantly. …"

PCA-CGAN model parameter settings. 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. …"

MIT-BIH dataset proportion analysis chart. 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. …"

Wavelet transform preprocessing 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. 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. …"

MIT dataset expansion quantities and Proportions. 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. …"

Experimental hardware and software environment. 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 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. …"

Classification model parameter settings. 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. …"

MIT-BIH expanded dataset proportion chart. 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. …"

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. …"