Authors
Sejuti Rahman, Sujan Sarker, Md Abdullah Al Miraj, Ragib Amin Nihal, AKM Nadimul Haque, Abdullah Al Noman
Publication date
2021/3/2
Source
Cognitive Computation
Pages
1-30
Publisher
Springer US
Description
The COVID-19 pandemic has wreaked havoc on the whole world, taking over half a million lives and capsizing the world economy in unprecedented magnitudes. With the world scampering for a possible vaccine, early detection and containment are the only redress. Existing diagnostic technologies with high accuracy like RT-PCRs are expensive and sophisticated, requiring skilled individuals for specimen collection and screening, resulting in lower outreach. So, methods excluding direct human intervention are much sought after, and artificial intelligence-driven automated diagnosis, especially with radiography images, captured the researchers’ interest. This survey marks a detailed inspection of the deep learning–based automated detection of COVID-19 works done to date, a comparison of the available datasets, methodical challenges like imbalanced datasets and others, along with probable solutions …
Total citations
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