How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future. (19th December 2020)
- Record Type:
- Journal Article
- Title:
- How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future. (19th December 2020)
- Main Title:
- How artificial intelligence may help the Covid‐19 pandemic: Pitfalls and lessons for the future
- Authors:
- Malik, Yashpal Singh
Sircar, Shubhankar
Bhat, Sudipta
Ansari, Mohd Ikram
Pande, Tripti
Kumar, Prashant
Mathapati, Basavaraj
Balasubramanian, Ganesh
Kaushik, Rahul
Natesan, Senthilkumar
Ezzikouri, Sayeh
El Zowalaty, Mohamed E.
Dhama, Kuldeep - Abstract:
- Summary: The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid‐19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI‐based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid‐19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI‐based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid‐19 cases. AI‐based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid‐19 pandemic.
- Is Part Of:
- Reviews in medical virology. Volume 31:Number 5(2021)
- Journal:
- Reviews in medical virology
- Issue:
- Volume 31:Number 5(2021)
- Issue Display:
- Volume 31, Issue 5 (2021)
- Year:
- 2021
- Volume:
- 31
- Issue:
- 5
- Issue Sort Value:
- 2021-0031-0005-0000
- Page Start:
- 1
- Page End:
- 11
- Publication Date:
- 2020-12-19
- Subjects:
- artificial intelligence -- covid‐19 -- epidemiology -- diagnosis -- SARS‐CoV‐2 -- therapeutic developments
Medical virology -- Periodicals
Review Literature -- Periodicals
Virus Diseases -- Periodicals
Viruses -- Periodicals
616.0194 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/rmv.2205 ↗
- Languages:
- English
- ISSNs:
- 1052-9276
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7792.500000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23809.xml