Graphs showing the temporal effects of temperature at the four different positions during a drilling sequence with guide drilling in two steps and final widening drilling (MIPS) an... by Marsel Ganeyev (21453399)

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A brief illustration of the revisions between AJCC TNM eighth and ninth editions. by Aihong Zheng (20571034)

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Baseline clinical and treatment features of patients with LLA ASCC. by Aihong Zheng (20571034)

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Increases in temperature for the two drill systems at different positions using different drilling procedures and feed rates. The data in bold indicate the position where the highe... by Marsel Ganeyev (21453399)

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Graphs showing the mean temperature increase at the positions with the highest mean temperature increase for the MIPS (A) and MONO (B) systems and three drilling protocols (DP1, DP... by Marsel Ganeyev (21453399)

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Fig 4 - by Aihong Zheng (20571034)

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Histologic evaluation of the osteotomy site. by Marsel Ganeyev (21453399)

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Patient selection flowchart. by Aihong Zheng (20571034)

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S2 Fig - by Aihong Zheng (20571034)

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(A-C) Force versus drill depth and torque versus drill depth. by Marsel Ganeyev (21453399)

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Increases in temperature for the two drill systems at different positions using different drilling procedures. The data in bold indicate the position where the highest mean tempera... by Marsel Ganeyev (21453399)

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Innovation and night light in large and small cities. by Saul Estrin (8629173)

Modeling results of 8-week-old female C57BL/6J mice. by Yan She (8639796)

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Sexual maturity status of female C57BL/6J Mice at different ages. by Yan She (8639796)

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Presents the bibliometric search results. by Yan She (8639796)

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Flow chart of data screening and analysis. by Yan She (8639796)

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S1 Data. Bibliometric analysis. S2 Data. Estrogen level analysis. S3 Data. MicroCT quantification. S4 Data. Markers of bone metabolism. by Yan She (8639796)

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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. …”