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robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
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lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary basic » binary mask (Expand Search)
basic robust » based robust (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
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141
Table 3_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx
Published 2025“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”
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142
Table 1_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx
Published 2025“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”
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143
Image 1_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.tif
Published 2025“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”
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144
Table 2_Constructing a neutrophil extracellular trap model based on machine learning to predict clinical outcomes and immune therapy responses in oral squamous cell carcinoma.xlsx
Published 2025“…Six machine learning algorithms were employed for model training, with the best model selected based on 1-year, 3-year, and 5-year AUC values. …”
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145
DataSheet1_Determination of a prediction model for therapeutic response and prognosis based on chemokine signaling-related genes in stage I–III lung squamous cell carcinoma.docx
Published 2022“…The TCIA database and pRRophetic algorithm were utilized to predict responses to immunochemotherapy and targeted therapy.…”
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146
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148
Data_Sheet_1_A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3.pdf
Published 2023“…This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. …”
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149
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Table_4_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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151
Image_2_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.tiff
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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152
Table_2_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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153
Image_1_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.tiff
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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154
Image_4_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.tiff
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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155
Table_1_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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156
Image_3_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.tiff
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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157
Table_3_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx
Published 2022“…</p>Methods<p>Specific hypoxia-related genes (sHRGs) were identified based on RNA-seq of OC cell lines cultured with different oxygen conditions. …”
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