The top 20 candidate drugs demonstrating the most significant sensitivity differences between high- and low-GSRS subjects. by Yu Zhang (12946)

Subjects:

Oscillatory potential (OP) analysis of 6-, 9-, and 12-month ERGs shows continued dysfunction in the inner retina reflecting A- and B-wave results. by Shaylah McCool (20818280)

Ni causes a decrease in membrane sterols in A549 lung epithelial cells. by Amber R. Matha (19681603)

Effects of students pre-University learning on current university progression. <i><i>Results displayed in percentages.</i></i> by Katy Andrews (22311170)

In BC tissue samples and BC cell lines, the expression of let-7b-5p decreased while the expression of AURKB increased. by Murat Kaya (578380)

Radial Ferrofluid Droplet Generation on a 2-D Star-Shaped Nozzle with 4 Vertices. by Amirhossein Favakeh (21417884)

Subjects:

Radial Ferrofluid Droplet Generation on a 2-D Star-Shaped Nozzle with 3 Vertices. by Amirhossein Favakeh (21417884)

Subjects:

CD74 regulates tumor progression. by Bianca Pellegrino (20314999)

Logistics regression analysis for the associations between decreased kidney function (eGFR < 90 mL/min/1.73 m²) and sex-specific z-scores of anthropometric indices, weig... by Xinyun Chen (6655703)

Average contact force and percentage of strong contact force under different conditions: (a) different particle shapes, (b) different particle sizes. by Yongfeng Zhu (7361045)

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. …”

Reducing Dscam1 diversity decreases adult lifespan in an exon-specific manner, Related to Fig 3. by Haiyang Dong (4783608)

Modeling the relationship between cancer level in hemolymph and MarBTN in tank eDNA. by Rachael M. Giersch (22331947)

Sequential viral exposure shapes immune cell profiles in tissues. by Yuhao Li (1559569)