Table 1_Impact of different 3D regions of interest on quantifying dynamic lumbar vertebral microstructure in ovariectomized rats—a micro-CT study.doc by Huihui Xu (778437)

“…However, whether different ROIs directly affect the results of quantitative micro-CT-based microarchitectural data is still unknown. …”

ROC curve of HPDL-MIAIHD method on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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Loss curve of HPDL-MIAIHD method on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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Confusion matrices of (a-b) 60:40 of TRAP/TESP and (c-d) 70:30 of TRAP/TESP. by Naif Almakayeel (16846021)

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ICH recognition outcome of HPDL-MIAIHD technique on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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Average of HPDL-MIAIHD methodology on 70:30 of TRAP/TESP. by Naif Almakayeel (16846021)

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Overall flow of the HPDL-MIAIHD approach. by Naif Almakayeel (16846021)

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outcome of HPDL-MIAIHD technique with recent methods [11–12]. by Naif Almakayeel (16846021)

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ICH recognition outcome of HPDL-MIAIHD methodology on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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curve of HPDL-MIAIHD methodology on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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Details on database. by Naif Almakayeel (16846021)

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Architecture of EfficientNet. by Naif Almakayeel (16846021)

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outcome of HPDL-MIAIHD technique with recent methods. by Naif Almakayeel (16846021)

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Average of HPDL-MIAIHD technique on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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PR curve of HPDL-MIAIHD method on 60:40 of TRAP/TESP. by Naif Almakayeel (16846021)

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Data Sheet 1_Changes in pancreatic levodopa uptake in patients with obesity and new-onset type 2 diabetes: an 18F-FDOPA PET-CT study.docx by Yeongkeun Kwon (3611216)

“…</p>Results<p>Pancreatic levodopa uptake increased in obese patients with insulin resistance, whereas it decreased in obese patients with new-onset type 2 diabetes [standardized uptake value (SUV) mean in participants with normal weight, 2.6 ± 0.7; SUV_mean in patients with obesity, 3.6 ± 0.1; SUV_mean in patients with obesity and new-onset type 2 diabetes, 2.6 ± 0.1, P = 0.02].…”

Table 1_Development of a clinical prediction model for poor treatment outcomes in the intensive phase in patients with initial treatment of pulmonary tuberculosis.docx by Bin Lu (65603)

“…Logistic regression analysis identified several independent risk factors for poor treatment outcomes, including diabetes, cavities in the lungs, tracheobronchial TB, increased C-reactive protein, and decreased hemoglobin. The AUC values were 0.815 for the modeling group and 0.851 for the validation group. …”

DDX5 and DDX17 decrease viral gene expression during KSHV lytic reactivation in iSLK.219 cells. by Praneet Kaur Sandhu (21156149)

Image 1_Iodine-131 induces ferroptosis and synergizes with sulfasalazine in differentiated thyroid cancer cells via suppressing SLC7A11.tif by Li Ling (424480)

Structure model predictions of wildtype and A398E/V and M1425V/I Ca_V3.3 channels. by Yousra El Ghaleb (22075892)