Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training.

Journal: Mycoses
Published Date: Oct 31, 2022

Abstract

BACKGROUND: Currently, the diagnosis of invasive pulmonary aspergillosis (IPA) mainly depends on the integration of clinical, radiological and microbiological data. Artificial intelligence (AI) has shown great advantages in dealing with data-rich biological and medical challenges, but the literature on IPA diagnosis is rare.

Authors

  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Mujiao Li
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Peimin Fan
    Department of Information Center, Guangzhou Chest Hospital, Guangzhou, China.
  • Hua Wang
    Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Jing Cai
    Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
  • Kai Wang
    Department of Rheumatology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
  • Tao Zhang
    Department of Traumatology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, 40044, People's Republic of China.
  • Zelin Xiao
    Department of Surgery, Guangzhou Chest Hospital, Guangzhou, China.
  • Jingdong Yan
    Department of Information, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Chaomin Chen
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Qingwen Lv
    Department of Information, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

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