بدائل البحث:
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
predicted decrease » predicted secreted (توسيع البحث), reported decrease (توسيع البحث)
higher decrease » higher degree (توسيع البحث), higher degrees (توسيع البحث), highest increase (توسيع البحث)
significantly predicted » significantly reduced (توسيع البحث), significantly reduce (توسيع البحث), significant predictor (توسيع البحث)
predicted decrease » predicted secreted (توسيع البحث), reported decrease (توسيع البحث)
higher decrease » higher degree (توسيع البحث), higher degrees (توسيع البحث), highest increase (توسيع البحث)
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Baseline characteristics and potential independent risk factors for mortality of SFTS.
منشور في 2025الموضوعات: -
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Kinetics of coagulation parameters between the survivors and non-survivors during hospitalization.
منشور في 2025الموضوعات: -
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Restricted cubic spline models depicting the relationship between APTT and mortality risk in SFTS.
منشور في 2025الموضوعات: -
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Kaplan-Meier survival analysis curves according to the APTT levels between four groups.
منشور في 2025الموضوعات: -
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Dynamic profile of coagulation parameters between survivors and non-survivors in patients with SFTS.
منشور في 2025الموضوعات: -
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Multivariate logistic regression analysis on the risk factors associated with prolonged APTT.
منشور في 2025الموضوعات: -
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Characteristics and outcomes of participants categorized by serum APTT on admission.
منشور في 2025الموضوعات: -
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SARIMA predicts season components.
منشور في 2025"…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …"
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Analysis of raw data prediction results.
منشور في 2025"…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …"
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Analysis of STL-PCA prediction results.
منشور في 2025"…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …"