COVIDX: Computer-aided diagnosis of Covid-19 and its severity prediction with raw digital chest X-ray images
Wajid Arshad Abbasi, Syed Ali Abbas, Saiqa Andleeb

TL;DR
COVIDX is an automated system utilizing deep learning on chest X-ray images to diagnose COVID-19, distinguish it from other conditions, and predict its severity, outperforming existing methods in various validation settings.
Contribution
This study introduces COVIDX, a novel three-phase deep learning-based system for COVID-19 diagnosis and severity prediction using chest X-ray images, with extensive validation and accessibility.
Findings
COVIDX outperforms existing methods in all validation settings.
The system effectively distinguishes COVID-19 from pneumonia and healthy cases.
COVIDX is accessible via a cloud webserver and open-source code.
Abstract
Coronavirus disease (COVID-19) is a contagious infection caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) and it has infected and killed millions of people across the globe. In the absence of specific drugs or vaccines for the treatment of COVID-19 and the limitation of prevailing diagnostic techniques, there is a requirement for some alternate automatic screening systems that can be used by the physicians to quickly identify and isolate the infected patients. A chest X-ray (CXR) image can be used as an alternative modality to detect and diagnose the COVID-19. In this study, we present an automatic COVID-19 diagnostic and severity prediction (COVIDX) system that uses deep feature maps from CXR images to diagnose COVID-19 and its severity prediction. The proposed system uses a three-phase classification approach (healthy vs unhealthy, COVID-19 vs Pneumonia, and…
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Taxonomy
TopicsCOVID-19 diagnosis using AI · Radiomics and Machine Learning in Medical Imaging · Anomaly Detection Techniques and Applications
