COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization
Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the lives of millions of people worldwide in the last 2 years. Because of the disease's rapid spread, it is critical to diagnose it at an early stage in order to reduce the rate of spread. The images of the lung...
Main Authors: | Ameer Hamza, Muhammad Attique Khan, Shui-Hua Wang, Abdullah Alqahtani, Shtwai Alsubai, Adel Binbusayyis, Hany S. Hussein, Thomas Markus Martinetz, Hammam Alshazly |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-08-01
|
Series: | Frontiers in Public Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.948205/full |
Similar Items
-
COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization
by: Ameer Hamza, et al.
Published: (2022-11-01) -
COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans
by: Hammam Alshazly, et al.
Published: (2021-07-01) -
Trading Stocks Based on Financial News Using Attention Mechanism
by: Saurabh Kamal, et al.
Published: (2022-06-01) -
Data Clustering Using Moth-Flame Optimization Algorithm
by: Tribhuvan Singh, et al.
Published: (2021-06-01) -
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
by: Hammam Alshazly, et al.
Published: (2021-01-01)