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An AI-enabled research support tool for the classification system of COVID-19
The outbreak of COVID-19, a little more than 2 years ago, drastically affected all segments of society throughout the world. While at one end, the microbiologists, virologists, and medical practitioners were trying to find the cure for the infection; the Governments were laying emphasis on precautio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020488/ https://www.ncbi.nlm.nih.gov/pubmed/36935722 http://dx.doi.org/10.3389/fpubh.2023.1124998 |
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author | Tiwari, Arti Bhattacharjee, Kamanasish Pant, Millie Srivastava, Shilpa Snasel, Vaclav |
author_facet | Tiwari, Arti Bhattacharjee, Kamanasish Pant, Millie Srivastava, Shilpa Snasel, Vaclav |
author_sort | Tiwari, Arti |
collection | PubMed |
description | The outbreak of COVID-19, a little more than 2 years ago, drastically affected all segments of society throughout the world. While at one end, the microbiologists, virologists, and medical practitioners were trying to find the cure for the infection; the Governments were laying emphasis on precautionary measures like lockdowns to lower the spread of the virus. This pandemic is perhaps also the first one of its kind in history that has research articles in all possible areas as like: medicine, sociology, psychology, supply chain management, mathematical modeling, etc. A lot of work is still continuing in this area, which is very important also for better preparedness if such a situation arises in future. The objective of the present study is to build a research support tool that will help the researchers swiftly identify the relevant literature on a specific field or topic regarding COVID-19 through a hierarchical classification system. The three main tasks done during this study are data preparation, data annotation and text data classification through bi-directional long short-term memory (bi-LSTM). |
format | Online Article Text |
id | pubmed-10020488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100204882023-03-18 An AI-enabled research support tool for the classification system of COVID-19 Tiwari, Arti Bhattacharjee, Kamanasish Pant, Millie Srivastava, Shilpa Snasel, Vaclav Front Public Health Public Health The outbreak of COVID-19, a little more than 2 years ago, drastically affected all segments of society throughout the world. While at one end, the microbiologists, virologists, and medical practitioners were trying to find the cure for the infection; the Governments were laying emphasis on precautionary measures like lockdowns to lower the spread of the virus. This pandemic is perhaps also the first one of its kind in history that has research articles in all possible areas as like: medicine, sociology, psychology, supply chain management, mathematical modeling, etc. A lot of work is still continuing in this area, which is very important also for better preparedness if such a situation arises in future. The objective of the present study is to build a research support tool that will help the researchers swiftly identify the relevant literature on a specific field or topic regarding COVID-19 through a hierarchical classification system. The three main tasks done during this study are data preparation, data annotation and text data classification through bi-directional long short-term memory (bi-LSTM). Frontiers Media S.A. 2023-03-03 /pmc/articles/PMC10020488/ /pubmed/36935722 http://dx.doi.org/10.3389/fpubh.2023.1124998 Text en Copyright © 2023 Tiwari, Bhattacharjee, Pant, Srivastava and Snasel. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Tiwari, Arti Bhattacharjee, Kamanasish Pant, Millie Srivastava, Shilpa Snasel, Vaclav An AI-enabled research support tool for the classification system of COVID-19 |
title | An AI-enabled research support tool for the classification system of COVID-19 |
title_full | An AI-enabled research support tool for the classification system of COVID-19 |
title_fullStr | An AI-enabled research support tool for the classification system of COVID-19 |
title_full_unstemmed | An AI-enabled research support tool for the classification system of COVID-19 |
title_short | An AI-enabled research support tool for the classification system of COVID-19 |
title_sort | ai-enabled research support tool for the classification system of covid-19 |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020488/ https://www.ncbi.nlm.nih.gov/pubmed/36935722 http://dx.doi.org/10.3389/fpubh.2023.1124998 |
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