Article: Artificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic.
Healthcare (Basel, Switzerland)
2023 Volume 11, Issue 6
Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to ... ...
| Abstract | The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to maximum severity of infection and surges in cases. Bacterial co-infection/secondary infection is identified during viral respiratory infection, which is a vital reason for morbidity and mortality. The occurrence of secondary infections is an additional burden to the healthcare system; therefore, the quick diagnosis of both COVID-19 and secondary infections will reduce work pressure on healthcare workers. Therefore, well-established support from Artificial Intelligence (AI) could reduce the stress in healthcare and even help in creating novel products to defend against the coronavirus. AI is one of the rapidly growing fields with numerous applications for the healthcare sector. The present review aims to access the recent literature on the role of AI and how its subfamily machine learning (ML) and deep learning (DL) are used to curb the pandemic's effects. We discuss the role of AI in COVID-19 infections, the detection of secondary infections, technology-assisted protection from COVID-19, global laws and regulations on AI, and the impact of the pandemic on public life. |
|---|---|
| Language | English |
| Publishing date | 2023-03-14 |
| Publishing country | Switzerland |
| Document type | Journal Article ; Review |
| ZDB-ID | 2721009-1 |
| ISSN | 2227-9032 |
| ISSN | 2227-9032 |
| DOI | 10.3390/healthcare11060854 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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