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.
Highlights
A novel coronavirus known as COVID-19 has been a global health threat since 2019. is virus produces severe acute respiratory syndrome
Multiorgan and respiratory system failure occur in critical conditions that may result in death. e risk of acute or critical sickness is more than 50% among those over the age of 40, according to statistics from the National Center for Health Statistics (NCHS)
Data Preparation and Model Inputs. e proposed dataset that contains X-ray images is collected in the first stage and divided into two classes. e infected images are divided into two classes, i.e., COVID-19 and influenza. 70% of data were utilized for model training, while 30% was used for testing purposes
Summary
A novel coronavirus known as COVID-19 has been a global health threat since 2019. is virus produces severe acute respiratory syndrome. A novel approach for detecting COVID-19 was proposed using publicly available chest X-ray and CT images by [13], which compared various DL feature extraction methods to find the most accurate features. Is article aims to build deep learning algorithms (CNN and LSTM) for detecting normal, influenza, and COVID-19 cases from X-ray images. Is article used deep learning techniques on X-ray images of COVID-19 and influenza for classification and detection. Influenza can be detected by chest X-ray images using proposed models like COVID-19. Brunese et al [18] presented the deep learning approach for COVID-19 detection from X-ray images. Is study investigates deep learning algorithms for autonomously processing chest X-ray images providing doctors with more reliable tools for screening COVID-19 patients and detecting confirmed instances.
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