Author: Min Zhou; Yong Chen; Dexiang Wang; Yanping Xu; Weiwu Yao; Jingwen Huang; Xiaoyan Jin; Zilai Pan; Jingwen Tan; Lan Wang; Yihan Xia; Longkuan Zou; Xin Xu; Jingqi Wei; Mingxin Guan; Jianxing Feng; Huan Zhang; Jieming Qu
Title: Improved deep learning model for differentiating novel coronavirus pneumonia and influenza pneumonia Document date: 2020_3_30
ID: ilc2bzkx_38
Snippet: The AUCs were much higher than the AUCs on the lesion level owing to the ensemble effect. For both schemes, the sensitivity is 100%. The specificities were 92.5% and 95% for the Plain and Trinary scheme, respectively (Table E8) Figure 3C ). Importantly, Trinary scheme performed better (AUC 0.91) than Plain scheme (AUC 0.87) on the second category (data was not from centers included in the training set) ( Figure 3D ). In terms of F1 . CC-BY-NC-ND .....
Document: The AUCs were much higher than the AUCs on the lesion level owing to the ensemble effect. For both schemes, the sensitivity is 100%. The specificities were 92.5% and 95% for the Plain and Trinary scheme, respectively (Table E8) Figure 3C ). Importantly, Trinary scheme performed better (AUC 0.91) than Plain scheme (AUC 0.87) on the second category (data was not from centers included in the training set) ( Figure 3D ). In terms of F1 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
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