Search alternatives:
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
nn decrease » _ decrease (Expand Search), gy decreased (Expand Search), b1 decreased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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8221
Effects of extracorporeal shock wave therapy on motor function in patients with cerebral palsy: a systematic review and meta-analysis
Published 2025“…In addition, spasticity significantly decreases, particularly with focused ESWT or ESWT targeting the upper limbs.…”
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8222
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8223
Supplementary tables: Assessing healthcare resource utilization burden and unmet treatment needs in patients with Parkinson’s disease: results from a real-world study
Published 2025“…The intermediate versus early group had a significantly greater proportion of patients with unmet treatment needs (p < 0.001), e.g., slowing disease progression, providing neuroprotection. …”
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8224
Supplementary data: Assessing healthcare resource utilization burden and unmet treatment needs in patients with Parkinson’s disease: results from a real-world study
Published 2025“…The intermediate versus early group had a significantly greater proportion of patients with unmet treatment needs (p < 0.001), e.g., slowing disease progression, providing neuroprotection. …”
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8225
Table 1_Association between life’s crucial 9 and sarcopenia: estimated glucose disposal rate as a key mediator.doc
Published 2025“…In crude models, each 10-point increase in LC9 was associated with a 4.9% decrease in sarcopenia odds (OR: 0.951, p < 0.001). …”
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8226
Table 4_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8227
Table 6_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8228
Table 5_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8229
Table 1_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8230
Image 1_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.tif
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8231
Table 3_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8232
Table 2_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx
Published 2025“…</p>Objective<p>To assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.…”
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8233
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8234
Parameters of VMR separated by light or dark periods run at 6 dpf.
Published 2025“…(E-H) VMR parameters in dnVDRa induced zebrafish at 48 hpf. There is a significant decrease in distance moved in the dark (p < 0.01) and light (p < 0.05) periods, a significant decrease in velocity in the dark (p < 0.05) and light (p < 0.01) periods, a significant decrease in activity state in the dark (p < 0.05) and light (p < 0.01) periods and a significant increase in distance to point in the light period (p < 0.01) in the 48 + fish. …”
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8235
PCA-CGAN model parameter settings.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”
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8236
MIT-BIH dataset proportion analysis chart.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”
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8237
Wavelet transform preprocessing results.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”
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8238
PCAECG_GAN.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”
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8239
MIT dataset expansion quantities and Proportions.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”
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8240
Experimental hardware and software environment.
Published 2025“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”