The optimal size of the reference cohort for calculating the network impact of a single sample. by Shir Ezra (18699696)

“…The AUC value for each pair of distributions is reported beneath. a) For Δ<i>S</i>, the AUC values are the highest for <i>m</i> = 50 and <i>m</i> = 100. b) For Δ<i>W</i>, the AUC values are the highest for <i>m</i> = 50 and <i>m</i> = 100. c) For <i>θ</i>, the AUC values increase for larger <i>m</i>, and for <i>m</i> ≥ 50 they are larger compared with those of the other network impact parameters.…”

⁶⁸Ga-Labeled TMTP1 Derivatives with Moderate Hydrophilicity for Positron Emission Tomography of Hepatocellular Carcinoma in High Contrast by Xiaowei Fan (10198883)

“…Herein, five ⁶⁸Ga-labeled polyethylene glycol (PEG)-modified derivatives of the TMTP1 peptide were synthesized. The log <i>D</i> values decreased from −1.70 (non-PEGylated) to −1.97 to −2.94 corresponding to the increase of PEG chain length. …”

Expression of miSS in human tissues. by Aleksei Mironov (10536039)

“…FDR cutoff of 5% is shown by the dashed curve. The <i>φ</i> value decreases with increase of <i>r</i>_<i>maSS</i> (right). …”

Normalized avalanche size with respect to changes in (<i>t</i>/<i>f</i>) value. by Heesuk Kang (18086720)

“…In the trade network, following the occurrence of a failure in the first country, as the (<i>t</i>/<i>f</i>) value decreases, the countries to which the failure is transmitted are displayed. …”

Figure 2 from mTORC1-Driven Protein Translation Correlates with Clinical Benefit of Capivasertib within a Genetically Preselected Cohort of <i>PIK3CA</i>-Altered Tumors by Constance A. Sobsey (19373550)

“…Node size increases as the <i>P</i>-value decreases. <b>B,</b> Top 20 canonical pathways that are significantly differentially activated between clinical benefit (CB) and no clinical benefit (NCB) groups, based on assessment with Fisher’s exact test in Qiagen IPA. …”

Table_4_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Table_6_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation by Yu Lin (370243)

“…When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). …”

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation by Yu Lin (370243)

“…When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). …”

Table_3_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Table_8_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation by Yu Lin (370243)

“…When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). …”

Table_1_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Image_2_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…The highest ACC value increased from 0.817 to 0.919 (12.5% increase), the highest area under ROC curve (AUC) value increased from 0.87 to 0.94 (8.0% increase), and all evaluation metrics improved by approximately 10% after being processed by our proposed gene selection algorithm. …”

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation by Yu Lin (370243)

“…When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). …”

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation by Yu Lin (370243)

“…When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748–0.921) and 0.847 (95% CI, 0.766–0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690–0.892). …”

Table_2_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Table_7_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Table_9_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xlsx by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”

Table_5_Prioritizing key synergistic circulating microRNAs for the early diagnosis of biliary tract cancer.xls by Fei Su (106529)

“…In the internal feature evaluation dataset, the area under the receiver operating characteristic curve (AUC) for each single miRNA was 0.8413 (hsa-let-7c-5p), 0.7143 (hsa-miR-16-5p), 0.8571 (hsa-miR-17-5p), and 0.9365 (hsa-miR-26a-5p), respectively, whereas the synergistic AUC value increased to 1.0000. In the internal test dataset, the single AUC was 0.6500, 0.5125, 0.6750, and 0.7500, whereas the synergistic AUC increased to 0.8375. …”