International Journal of Medical Research & Health Sciences (IJMRHS)
ISSN: 2319-5886 Indexed in: ESCI (Thomson Reuters)
Marwan A. Albahar
College of Computers at Al-Leith, Umm Al Qura University, Mecca, Saudi ArabiaPublications
-
Research
An Ensemble Model for Detecting Coronavirus disease-19 from Chest X-ray Images
Author(s): Marwan A. Albahar*, Mohammed I. Thanoon and Abdulaziz A. Albahr
In current times, novel Coronavirus Disease-19 (COVID-19) has become one of the world’s biggest challenges. The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) which causes this disease results in high mortality and morbidity rates globally. It has been revealed from the study that patients infected with COVID-19 exhibit different radiographic visual characteristics along with dyspnea, fatigue, dry cough, fever, etc. In this account, Chest X-Ray (CXR) is considered as one of the most significant, non-invasive clinical methods that assist in detecting the visual responses that are related to SARS-CoV-2 infection. However, the radiologist’s and experts’ minimal availability and experts’ ability to interpret the CXR images and subtle images of the disease serve as the prominent hurdles in manual diagnosis. This study presents an automatic coronavirus .. Read More»
Select your language of interest to view the total content in your interested language