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A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation

The VOIs, including the abdominal aorta (including the 3 main branches of the celiac trunk and the primary branches of the SMA and the IMA) and the bowel (including the jejunum, ileum, and colon), were manually labeled by a surgeon (Z Jin, reader 1) with 5 years of diagnostic experience using a 3 D Slicer. To validate annotation consistency [28], a second surgeon (YJ, reader 2) independently labeled a randomly selected subset (n=30) of images.

Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

J Med Internet Res 2025;27:e72649

Smart Technology Facilitated Patient-Centered Venous Thromboembolism Management (the SmaVTE Study): Protocol for a Randomized Controlled Trial

Smart Technology Facilitated Patient-Centered Venous Thromboembolism Management (the SmaVTE Study): Protocol for a Randomized Controlled Trial

VTE events are categorized into 3 groups: new-onset VTE, hospital-acquired VTE (HA-VTE), and recurrent VTE. VTE that occurred for the first time during the study period is classified as new-onset VTE. HA-VTE is defined as any new-onset VTE that has occurred within 90 days of hospital discharge [4]. Recurrent VTE is defined as the appearance of new evidence of VTE after acute VTE has been treated in the acute phase (2 weeks) with significant clinical improvement in signs and symptoms.

Zhi-Geng Jin, Zhe-Qi Zhang, Bin-Bin Liu, Hao Wang, Ying Yang, Li-Na Ren, Hui Zhang, Wei Ji, Zhen-Guo Zhai, Yu-Tao Guo

JMIR Res Protoc 2025;14:e67254