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Computer-aided methods for combating Covid-19 in prevention, detection, and service provision approaches
Bahareh Rezazadeh1, Parvaneh Asghari2, Amir Masoud Rahmani3
1Computer Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Neural Computing & Applications
|June 5, 2023
Summary
Computer-aided methods, including artificial intelligence (AI), are crucial for managing the COVID-19 pandemic. This survey explores AI, machine learning, and deep learning applications for disease prevention, detection, and healthcare services.
Area of Science:
- Computer Science
- Public Health
- Artificial Intelligence
Background:
- The COVID-19 pandemic has caused unprecedented global disruption since 2019.
- National responses varied based on resources and infrastructure.
- Effective pandemic control necessitates intelligent, automated healthcare systems.
Purpose of the Study:
- To survey computer-based strategies for combating COVID-19.
- To analyze methods for prevention, detection, and service provision.
- To provide a technical taxonomy and identify future research directions.
Main Methods:
- Review of computer-aided methods leveraging AI, machine learning, and deep learning.
- Analysis of Internet of Things (IoT) and fog-cloud computing applications.
- Categorization and technical taxonomy of current approaches.
Main Results:
- Shift from initial lockdowns to advanced computer-aided monitoring and treatment.
- Integration of AI, IoT, and fog-cloud computing for healthcare services.
- Identification of key methods for disease prevention and detection.
Conclusions:
- Computer-based approaches are essential for modern pandemic management.
- AI, machine learning, and deep learning offer powerful tools for COVID-19 response.
- Further research is needed to address open issues in intelligent healthcare systems.
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