بدائل البحث:
marker decrease » marked decrease (توسيع البحث), larger decrease (توسيع البحث), marked increase (توسيع البحث)
values decrease » values increased (توسيع البحث), largest decrease (توسيع البحث)
learning test » learning task (توسيع البحث), learning tasks (توسيع البحث), learning rates (توسيع البحث)
test decrease » teer decrease (توسيع البحث), cost decreased (توسيع البحث), mean decrease (توسيع البحث)
a marker » _ marker (توسيع البحث), _ markers (توسيع البحث)
i values » _ values (توسيع البحث)
marker decrease » marked decrease (توسيع البحث), larger decrease (توسيع البحث), marked increase (توسيع البحث)
values decrease » values increased (توسيع البحث), largest decrease (توسيع البحث)
learning test » learning task (توسيع البحث), learning tasks (توسيع البحث), learning rates (توسيع البحث)
test decrease » teer decrease (توسيع البحث), cost decreased (توسيع البحث), mean decrease (توسيع البحث)
a marker » _ marker (توسيع البحث), _ markers (توسيع البحث)
i values » _ values (توسيع البحث)
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Validation of genetic markers for risk of OA or knee OA for decrease in minJSW.
منشور في 2025"…<p><b>(A)</b> Manhattan plot of minJSW decrease at 24 months. The Manhattan plots show the -log10(P) values of all ~ 1,5 million SNPs against their position. …"
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Image 1_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif
منشور في 2025"…</p>Results<p>In total, 15 types of decreased autoantibodies were identified, and 6 of them were constructed into a predictive model for early lung cancer, reaching a sensitivity of 76.19% and a specificity of 55.74%. …"
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<i>SLC2A2</i> is essential for liver differentiation in developing vertebrates
منشور في 2025الموضوعات: -
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The MAE value of the model under raw data.
منشور في 2025"…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …"
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Three error values under raw data.
منشور في 2025"…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …"
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