Selected article for: "absolute neutrophil number and Patient age"
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_11
    Snippet: Artificial intelligence (AI) may provide a method to augment early detection of SARS-CoV-2 infection. Our goal was to design an AI model that can identify SARS-CoV-2 infection based on the initial chest CT scans and associated clinical information that could rapidly identify SARS-CoV-2 (+) patients in the early stage. We collected chest CT scans and corresponding clinical information obtained at patient presentation. Clinical information included.....
    Document: Artificial intelligence (AI) may provide a method to augment early detection of SARS-CoV-2 infection. Our goal was to design an AI model that can identify SARS-CoV-2 infection based on the initial chest CT scans and associated clinical information that could rapidly identify SARS-CoV-2 (+) patients in the early stage. We collected chest CT scans and corresponding clinical information obtained at patient presentation. Clinical information included travel and exposure history, leukocyte counts (including absolute neutrophil number, neutrophil percentage, absolute lymphocyte number, and lymphocyte percentage), symptomatology (presence of fever, cough, and sputum), patient age, and patient sex.

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