A Survey on DL Based Frameworks for COVID-19 Radiological Diagnosis
6th IFIP TC 5 International Conference on Computer, Communication, and Signal Processing, ICCSP 2022
; 651 IFIP:36-45, 2022.
Article
in English
| Scopus | ID: covidwho-1971576
ABSTRACT
The ongoing Coronavirus disease (COVID-19) pandemic still necessitates emphasis on diagnosis and management of the outbreaks due to the emergence of new variants. This paper is an extensive survey on the implementation of Deep Learning (DL) models used for diagnosing COVID-19 from chest imaging, enriched with quantitative measures and regulatory aspects. The authors have searched, collated and categorised various models and techniques that reported different architectures with respect to COVID-19 diagnosis in the literature. This survey also briefs about quantifying metrics and the reported results are enumerated, also regulatory frameworks for public use of Artificial Intelligence (AI) in medical devices are comprehended. © 2022, IFIP International Federation for Information Processing.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Observational study
Language:
English
Journal:
6th IFIP TC 5 International Conference on Computer, Communication, and Signal Processing, ICCSP 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS