Significant associations in GWAS. by Dai Nogimura (21445649)

“…<div><p>Decreased nitric oxide (NO) production from the vascular endothelium is a major factor for vascular aging. …”

Comparison of actual vs predicted values after transfer. by Bin Pan (742525)

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Pan-cancer analyses of ACADM expression and its prognostic significance in the TCGA database. by Yu Zhang (12946)

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Ordinal regression predictions. by Thierry Jean (20691795)

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Binary classification predictions. by Thierry Jean (20691795)

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Pan-cancer analyses of ANGPTL4 expression and its prognostic significance in the TCGA database. by Yu Zhang (12946)

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Pan-cancer analyses of NFKB2 expression and its prognostic significance in the TCGA database. by Yu Zhang (12946)

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Predicted <i>cis</i>-acting elements in <i>DpAP2</i> promoter. by Lingru Ruan (18995544)

Patients’ demographics and clinical parameters. by Zi-Rong Chen (9227618)

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Percent change in yearly crude rates (between 2019 and 2021 and between 2019 and 2024) by gender and state. by Tony Wong (779773)

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Comparison of measured and predicted values of empirical model prediction. by Hongqi Wang (2208238)

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Average mean decrease Gini across 100 partitions for the top 10 most important variables for binary mixed model and random forest. by Helal El-Zaatari (20442243)

Exposure to biologics during pregnancy does not affect placental antibody transfer of anti-SARS-CoV-2 neutralizing antibodies, but concomitant corticosteroid exposure may decrease... by Donna E. Leet (22772478)

Identification of ACADM, ANGPTL4, and NFKB2 as significant predictors of OS in the TCGA-KIRC cohort. by Yu Zhang (12946)

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Data. by Su Hwan Park (15158181)

“…Participants in the progression group were younger (60.7 vs. 65.7 years, P = 0.015) and showed a larger BCVA change (0.20 vs. 0.04, P < 0.001) and greater ERM area decrease (34.2% vs. 11.7%, P < 0.001) during the follow-up period. …”

Baseline characteristics of patients. by Su Hwan Park (15158181)

“…Participants in the progression group were younger (60.7 vs. 65.7 years, P = 0.015) and showed a larger BCVA change (0.20 vs. 0.04, P < 0.001) and greater ERM area decrease (34.2% vs. 11.7%, P < 0.001) during the follow-up period. …”

Decreasing oxygen saturation with corresponding levels of NLR and D-dimer for understanding the interplay of inflammation. by Narendran Gopalan (110148)

Changes in best-corrected visual acuity and total area reduction ratio of the epiretinal membrane (ERM) during follow-up. by Su Hwan Park (15158181)

Workflow diagram of the prediction algorithm framework. by Bin Pan (742525)

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ROC Results Predicted in the Sample. by Fangyi Yang (18867853)

“…The model estimation results indicate that passenger patience significantly influences drop-off decisions. All models—static, dynamic, and Cox proportional hazards—achieved prediction accuracies exceeding 70%, with the dynamic model outperforming others when ample sample data is available. …”