The growth of co-transformed cells in the peritoneal cavity alters viral gene expression to mirror that of PEL cell lines. by Mitchell Hayes (5334887)

Co-transformed cells grow preferentially as tumors in peritoneal cavities. by Mitchell Hayes (5334887)

The growth of co-transformed cells in the peritoneal cavity alters their cellular gene expression to mirror that of PEL biopsies. by Mitchell Hayes (5334887)

Co-infected cells express both KSHV and EBV genes <i>in vitro</i> necessary for their survival and growth. by Mitchell Hayes (5334887)

Forest Plot of Multivariate Odds Ratios for Risk Factors Associated with Nerve Injury 90 Days After Total Knee Arthroplasty. by Rahul H. Jayaram (21463899)

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PVS_ratio changes, ΔPVS_ratio, for different radiation doses within each treatment period: 0M–3M(a), 3M–12M(b), and 12M–FollowUp(c). by Ruitian Song (11045127)

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Patient demographic information at four time points. by Ruitian Song (11045127)

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T1w images (top row) and segmented PVS overlaid on T1w images (bottom row) at TP of 0M, 3M, 12M, and FollowUp for a typical patient. by Ruitian Song (11045127)

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Box plots representing comparisons of PVS volumes across different variables with statistical comparison annotations for TP(a), DOSE(b), Shunt(c), Anesthesia(d), and Sex(e). by Ruitian Song (11045127)

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PVS ratio comparisons across different variables using box plots with statistical comparison annotations for TP(a), DOSE(b), Shunt(c), Anesthesia(d), and Sex(e). by Ruitian Song (11045127)

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PVS_volume changes, ΔPVS_volumes, for various radiation doses within each treatment period: 0M–3M(a), 3M–12M(b), and 12M–FollowUp(c). by Ruitian Song (11045127)

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Univariate and Multivariate analysis of risk factors for nerve injury 90-days after TKA. by Rahul H. Jayaram (21463899)

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The dataset for the paired model. by Ruitian Song (11045127)

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Patient enrollment and inclusion information. by Ruitian Song (11045127)

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Changes of PVS ratios and volumes for different treatment periods and different dose levels (HD: high dose, SD: standard dose, and RD: reduced dose). by Ruitian Song (11045127)

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The dataset for the full model analysis. by Ruitian Song (11045127)

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Table 1_The development of the neurosurgery workforce in Austria over the past quarter century: is more always better?.xlsx by Mario Mischkulnig (11659318)

Architecture of Swin-T model. by Wen-Qing Huang (5258126)

“…Experimental results demonstrate that compared to the baseline model, the proposed enhanced model achieves a reduction of 2.5G Flops computational complexity and a 16% speed improvement on a private pavement disease dataset, with only a 1.2 percentage point decrease in AUC accuracy. Moreover, compared to other mainstream image classification models, this model exhibits more balanced performance on a public dataset, with improved accuracy and speed that better align with the practical requirements of pavement inspection. …”

Model the experimental results curve. by Wen-Qing Huang (5258126)

“…Experimental results demonstrate that compared to the baseline model, the proposed enhanced model achieves a reduction of 2.5G Flops computational complexity and a 16% speed improvement on a private pavement disease dataset, with only a 1.2 percentage point decrease in AUC accuracy. Moreover, compared to other mainstream image classification models, this model exhibits more balanced performance on a public dataset, with improved accuracy and speed that better align with the practical requirements of pavement inspection. …”

Results of comparison experiments. by Wen-Qing Huang (5258126)

“…Experimental results demonstrate that compared to the baseline model, the proposed enhanced model achieves a reduction of 2.5G Flops computational complexity and a 16% speed improvement on a private pavement disease dataset, with only a 1.2 percentage point decrease in AUC accuracy. Moreover, compared to other mainstream image classification models, this model exhibits more balanced performance on a public dataset, with improved accuracy and speed that better align with the practical requirements of pavement inspection. …”