| Title |
Overview of current state of research on the application of artificial intelligence techniques for COVID-19 / |
| Authors |
Kumar, Vijay ; Singh, Dilbag ; Kaur, Manjit ; Damaševičius, Robertas |
| DOI |
10.7717/peerj-cs.564 |
| Full Text |
|
| Is Part of |
PeerJ computer science.. London : PeerJ. 2021, vol. 7, art. no. e564, p. 1-34.. ISSN 2376-5992 |
| Keywords [eng] |
Artificial intelligence ; Disease prediction ; Diagnosis ; Covid-19 |
| Abstract [eng] |
Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. Methodology: This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models. Results: In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences. Conclusions: The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients. |
| Published |
London : PeerJ |
| Type |
Journal article |
| Language |
English |
| Publication date |
2021 |
| CC license |
|
