Author: Lan, Lan; Sun, Wenbo; Xu, Dan; Yu, Minhua; Xiao, Feng; Hu, Huijuan; Xu, Haibo; Wang, Xinghuan
Title: Artificial intelligence-based approaches for COVID-19 patient management Cord-id: 7c9e5qr0 Document date: 2021_6_10
ID: 7c9e5qr0
Snippet: During the highly infectious pandemic of coronavirus disease 2019 (COVID-19), artificial intelligence (AI) has provided support in addressing challenges and accelerating achievements in controlling this public health crisis. It has been applied in fields varying from outbreak forecasting to patient management and drug/vaccine development. In this paper, we specifically review the current status of AI-based approaches for patient management. Limitations and challenges still exist, and further nee
Document: During the highly infectious pandemic of coronavirus disease 2019 (COVID-19), artificial intelligence (AI) has provided support in addressing challenges and accelerating achievements in controlling this public health crisis. It has been applied in fields varying from outbreak forecasting to patient management and drug/vaccine development. In this paper, we specifically review the current status of AI-based approaches for patient management. Limitations and challenges still exist, and further needs are highlighted.
Search related documents:
Co phrase search for related documents- accuracy achieve and lung involvement: 1
- accuracy rate and lung involvement: 1, 2
- accurate diagnosis and acute respiratory distress syndrome: 1, 2, 3, 4, 5, 6, 7, 8
- accurate diagnosis and acute respiratory distress syndrome coronavirus: 1
- accurate diagnosis and additional research need: 1
- accurate diagnosis and lung involvement: 1, 2
- acute respiratory distress syndrome and lung involvement: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- acute respiratory distress syndrome coronavirus and lung involvement: 1, 2, 3
Co phrase search for related documents, hyperlinks ordered by date