Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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2161
Red blood cell-platelet ratio and HR-restriction cube diagram during hospitalization.
Published 2025Subjects: -
2162
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2163
Prognostic Impact of Red Blood Cell-Platelet Ratio Trajectory Categories after PSM.
Published 2025Subjects: -
2164
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2165
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2166
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2167
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2168
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2169
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2170
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2174
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Data Sheet 1_Increasing Mu wave desynchronization after dance classes on people with Parkinson’s disease.pdf
Published 2025“…The results showed a statistically significant increase in Mu rhythm desynchronization in the alpha 1 band at the central channels after 6 months of dance classes. …”
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2177
Data Sheet 2_Increasing Mu wave desynchronization after dance classes on people with Parkinson’s disease.pdf
Published 2025“…The results showed a statistically significant increase in Mu rhythm desynchronization in the alpha 1 band at the central channels after 6 months of dance classes. …”
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2178
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2179
PCA-CGAN model parameter settings.
Published 2025“…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. …”
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2180
MIT-BIH dataset proportion analysis chart.
Published 2025“…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. …”