Diagnosis model of early Pneumocystis jirovecii pneumonia based on convolutional neural network: a comparison with traditional PCR diagnostic method.

Journal: BMC pulmonary medicine
PMID: 38664747

Abstract

BACKGROUND: Pneumocystis jirovecii pneumonia (PJP) is an interstitial pneumonia caused by pneumocystis jirovecii (PJ). The diagnosis of PJP primarily relies on the detection of the pathogen from lower respiratory tract specimens. However, it faces challenges such as difficulty in obtaining specimens and low detection rates. In the clinical diagnosis process, it is necessary to combine clinical symptoms, serological test results, chest Computed tomography (CT) images, molecular biology techniques, and metagenomics next-generation sequencing (mNGS) for comprehensive analysis.

Authors

  • Yingying Li
    Institute of Environment and Health, Jianghan University, Wuhan 430056, China.
  • Hailin Liu
    Department of Gastroenterology, Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200011, China.
  • Qingwen Lv
    Department of Information, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Jun Long

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