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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

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