Search alternatives:
significant linear » significant clinical (Expand Search), significant gender (Expand Search), significant level (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » greater decrease (Expand Search)
significant linear » significant clinical (Expand Search), significant gender (Expand Search), significant level (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » greater decrease (Expand Search)
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1921
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1922
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1923
Analysis of differential microbiome and classification prediction model between case and control groups.
Published 2025“…<p><b>(A)</b> Linear discriminant analysis [LDA; (log10)>2] and (B) effect size (LEfSe) analysis revealed significant differences (P < 0.01) in the microbiota of the case (orange, negative score) and control groups (blue, positive score) groups. …”
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1924
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1925
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1926
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1927
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1928
Questionnaire description.
Published 2025“…<div><p>Background</p><p>During the last decades, intensive care unit (ICU) mortality rates have significantly decreased but this progress has come with unintended consequences for patients and their caregivers. …”
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1929
Complexity comparison of different models.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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1930
Dynamic window based median filtering algorithm.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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1931
Flow of operation of improved KMA.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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1932
Improved DAE based on LSTM.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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1933
Autoencoder structure.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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1934
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1935
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1936
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1937
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1938
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1939
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1940