Automatic Detection of Cases of COVID-19 Pneumonia from Chest X-ray Images and Deep Learning Approaches.
Fahima HajjejSarra AyouniMalek HasanTanvir AbirPublished in: Computational intelligence and neuroscience (2022)
Machine learning has already been used as a resource for disease detection and health care as a complementary tool to help with various daily health challenges. The advancement of deep learning techniques and a large amount of data-enabled algorithms to outperform medical teams in certain imaging tasks, such as pneumonia detection, skin cancer classification, hemorrhage detection, and arrhythmia detection. Automated diagnostics, which are enabled by images extracted from patient examinations, allow for interesting experiments to be conducted. This research differs from the related studies that were investigated in the experiment. These works are capable of binary categorization into two categories. COVID-Net, for example, was able to identify a positive case of COVID-19 or a healthy person with 93.3% accuracy. Another example is CHeXNet, which has a 95% accuracy rate in detecting cases of pneumonia or a healthy state in a patient. Experiments revealed that the current study was more effective than the previous studies in detecting a greater number of categories and with a higher percentage of accuracy. The results obtained during the model's development were not only viable but also excellent, with an accuracy of nearly 96% when analyzing a chest X-ray with three possible diagnoses in the two experiments conducted.
Keyphrases
- deep learning
- machine learning
- healthcare
- artificial intelligence
- coronavirus disease
- convolutional neural network
- sars cov
- loop mediated isothermal amplification
- real time pcr
- high resolution
- label free
- big data
- public health
- magnetic resonance imaging
- physical activity
- mass spectrometry
- case report
- computed tomography
- single cell
- risk assessment
- atrial fibrillation
- electronic health record
- climate change
- ionic liquid
- health information
- respiratory failure
- respiratory syndrome coronavirus
- electron microscopy
- human health
- dual energy