Author: Cheng Jin; Weixiang Chen; Yukun Cao; Zhanwei Xu; Xin Zhang; Lei Deng; Chuansheng Zheng; Jie Zhou; Heshui Shi; Jianjiang Feng
Title: Development and Evaluation of an AI System for COVID-19 Document date: 2020_3_23
ID: k1lg8c7q_44
Snippet: Further, we provided a visual explanation of the system's decision by performing a radiomics analysis to obtain diagnostically relevant phenotypic characteristics of the attentional regions that are fully traceable on the original CT image. This is important for an in-depth study of pulmonary imaging findings in patients with COVID-19. For the AI system, by visualizing the diagnostic results of 200 subjects from the reader study cohort and compar.....
Document: Further, we provided a visual explanation of the system's decision by performing a radiomics analysis to obtain diagnostically relevant phenotypic characteristics of the attentional regions that are fully traceable on the original CT image. This is important for an in-depth study of pulmonary imaging findings in patients with COVID-19. For the AI system, by visualizing the diagnostic results of 200 subjects from the reader study cohort and comparing them with human reader in the reader study, together with the subsequent radiomics analysis, we were able to perform detailed imaging phenotype analysis on the diagnosis of COVID-19, and subsequently make pathophysiological and anatomical speculations on the viral infection process (see Feature Analysis in Methods).
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