Covid-19 diagnosis and clinical symptom expression levels in a deep learning model

Authors

  • Minh-Dat Le Chon Ho Chi Minh University of Technology (HCMUT) Ho Chi Minh University of Science (HCMUS)
  • Thai-Ngoc Nguyen Ho Chi Minh City University of Medicine and Pharmacy

Abstract

In December 2019, a new strain of virus called COVID-19 (previously designated as 2019-nCoV) caused the first detected outbreak in Wuhan City, Hubei Province, China and since then spread globally. Viruses can cause several types of damage to the respiratory tract, including Tracheitis; Bronchitis; Pneumonia. It is difficult to distinguish coronavirus pneumonia from some other microbiological causes through X-ray images. However, it can be distinguished from a normal person by chest X-ray and CT-Scan, along with clinical judgment through actual symptoms. The following article provides the process and setup of an analytical machine learning model and provides some clinical comparisons between the effectiveness of the machine learning model and the level of clinical symptomatology of a statistical sample. Medical records of some patients in Ho Chi Minh City, Vietnam.

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Published

2022-09-30

Issue

Vol. 16 No. 3 (2022): September 2022

Section

Computational Intelligence

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