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An AI-enabled research support tool for the classification system of COVID-19
Arti Tiwari1, Kamanasish Bhattacharjee2, Millie Pant1,3
1Department of Applied Mathematics and Scientific Computing, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India.
Frontiers in Public Health
|March 20, 2023
Summary
This study developed a research tool to help scientists quickly find COVID-19 literature using a hierarchical classification system. It employed data preparation, annotation, and bi-directional long short-term memory (bi-LSTM) for text classification.
Area of Science:
- Information Science
- Computational Biology
- Public Health
Background:
- The COVID-19 pandemic impacted global society, generating extensive research across diverse disciplines.
- Effective literature review is crucial for understanding and addressing pandemic-related challenges and future preparedness.
Purpose of the Study:
- To develop a research support tool for swift identification of relevant COVID-19 literature.
- To implement a hierarchical classification system for organizing research articles.
Main Methods:
- Data preparation and annotation of COVID-19 research articles.
- Text data classification using a bi-directional long short-term memory (bi-LSTM) model.
Main Results:
- A functional research support tool was created.
- The bi-LSTM model facilitated hierarchical classification of scientific literature.
Conclusions:
- The developed tool enhances researchers' ability to navigate the vast body of COVID-19 literature.
- This approach aids in better preparedness for future global health crises through efficient knowledge discovery.
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