Author: Xueyan Mei; Hao-Chih Lee; Kaiyue Diao; Mingqian Huang; Bin Lin; Chenyu Liu; Zongyu Xie; Yixuan Ma; Philip M. Robson; Michael Chung; Adam Bernheim; Venkatesh Mani; Claudia Calcagno; Kunwei Li; Shaolin Li; Hong Shan; Jian Lv; Tongtong Zhao; Junli Xia; Qihua Long; Sharon Steinberger; Adam Jacobi; Timothy Deyer; Marta Luksza; Fang Liu; Brent P. Little; Zahi A. Fayad; Yang Yang
Title: Artificial intelligence for rapid identification of the coronavirus disease 2019 (COVID-19) Document date: 2020_4_17
ID: 79tozwzq_13
Snippet: A dataset of the presenting chest CT scans from 905 patients for whom there was a clinical concern of SARS-CoV-2 was acquired between Jan 17, 2020 and March 3, 2020 from 18 medical centers in 13 provinces in China. The data set included patients aged from 1 year to 91 years (40.7 year ± 16.5 years), and included 488 men and 417 women. All subjects were acquired using a standard chest CT protocol and were reconstructed using the lung kernel and d.....
Document: A dataset of the presenting chest CT scans from 905 patients for whom there was a clinical concern of SARS-CoV-2 was acquired between Jan 17, 2020 and March 3, 2020 from 18 medical centers in 13 provinces in China. The data set included patients aged from 1 year to 91 years (40.7 year ± 16.5 years), and included 488 men and 417 women. All subjects were acquired using a standard chest CT protocol and were reconstructed using the lung kernel and displayed with a lung window.
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