The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting. by Razieh Bidhendi-Yarandi (7139387)

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Characteristics of studied included. by Razieh Bidhendi-Yarandi (7139387)

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Flowchart of the search process. by Razieh Bidhendi-Yarandi (7139387)

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Funnel plot for testing asymmetry hypothesis using Freeman-Tukey double arcsine transformation for proportions. by Razieh Bidhendi-Yarandi (7139387)

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Results of random effect meta-analysis using Freeman-Tukey double arcsine transformation for proportions, regardless of the duration of their symptoms. by Razieh Bidhendi-Yarandi (7139387)

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(A) Cardiovascular Disease and (B) type-2 Diabetes Mellitus, and (C) chronic kidney disease- related Age-Adjusted Mortality Rates per 100,000 in Adults in the United States, 1999 t... by Aman Goyal (19231397)

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Volitional control frequency and intensity in VH (Kapsner-Smith et al., 2025) by Mara R. Kapsner-Smith (22139315)

“…Singers produced significantly smaller mean smallest changes of both <i>F</i>0 and intensity than nonsingers.…”

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

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

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

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

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

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Architecture of Swin Transformer Block. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Disease distribution map of the GZDL-BD. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Token merging module. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Comparative results of the ablation experiments. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Log2 fold change (FC), mean and standard deviation (SD) of each lipid specie from the normal liver (NL) and metabolic dysfunction-associated steatohepatitis (MASH) groups, and adju... by Laia Bertran (3685147)

Log2 fold change (FC), mean and standard deviation (SD) of each lipid specie from the normal liver (NL) and simple steatosis (SS) groups, and adjusted p-values. by Laia Bertran (3685147)

Log2 fold change (FC), mean and standard deviation (SD) of each lipid specie from the normal liver (NL) and metabolic dysfunction-associated steatotic liver disease (MASLD) groups,... by Laia Bertran (3685147)

Log2 fold change (FC), mean and standard deviation (SD) of each lipid specie from the simple steatosis (SS) and metabolic dysfunction-associated steatohepatitis (MASH) groups, and... by Laia Bertran (3685147)

Positioning errors of different algorithms on the a multi-modal and multi-scenario dataset for ground robots dataset. by Hongliang Zou (20707270)

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Epac activation with 8CPT-AM induced RLC phosphorylation in the perfused hearts. by Yoshiki Ohnuki (576298)

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