Classification of COVID-19 and Influenza Patients Using Deep Learning.
Contrast Media Mol Imaging
; 2022: 8549707, 2022.
Article
in English
| MEDLINE | ID: covidwho-2248150
ABSTRACT
Coronavirus (COVID-19) is a deadly virus that initially starts with flu-like symptoms. COVID-19 emerged in China and quickly spread around the globe, resulting in the coronavirus epidemic of 2019-22. As this virus is very similar to influenza in its early stages, its accurate detection is challenging. Several techniques for detecting the virus in its early stages are being developed. Deep learning techniques are a handy tool for detecting various diseases. For the classification of COVID-19 and influenza, we proposed tailored deep learning models. A publicly available dataset of X-ray images was used to develop proposed models. According to test results, deep learning models can accurately diagnose normal, influenza, and COVID-19 cases. Our proposed long short-term memory (LSTM) technique outperformed the CNN model in the evaluation phase on chest X-ray images, achieving 98% accuracy.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Tomography, X-Ray Computed
/
Influenza, Human
/
Deep Learning
/
SARS-CoV-2
/
COVID-19
Type of study:
Experimental Studies
Topics:
Long Covid
Limits:
Female
/
Humans
/
Male
Language:
English
Journal:
Contrast Media Mol Imaging
Journal subject:
Diagnostic Imaging
Year:
2022
Document Type:
Article
Affiliation country:
2022
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