Publications on COVID-19 and artificial intelligence: trends and lessons

Purpose: This study investigates shifts in scientific research focus, particularly the decline in COVID-19-related research and the rapid growth of artificial intelligence (AI) publications.Methods: We analyzed publication data from the Web of Science, comparing yearly publication counts for COVID-19 and AI research. The study also tracked changes in the impact factors of leading journals like <i>Science</i> and <i>Nature</i>, alongside those of top AI journals over the past decade. Additionally, we reviewed the top 10 most cited articles in 2021 from <i>Science</i> and <i>Nature</i> and the most influential AI publications from the past five years according to Google Scholar. The impact trends of the top 100 AI journals in computer science were also explored.Results: The analysis reveals a noticeable decline in COVID-19 related publications as the pandemic urgency diminishes, contrasted with the continued rapid growth of AI research. Impact factors for prestigious journals have shifted, with AI journals increasingly dominating the academic landscape. The review of top-cited articles further emphasizes these trends.Conclusion: Our findings indicate a significant shift in research priorities, with AI emerging as a dominant field poised to address future challenges, reflecting the evolving focus of the scientific community.

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Publication Details

Journal
Science Editing
Published
2024-08-20
DOI
https://doi.org/10.6087/kcse.338
Citations
1
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.40

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article

Publications on COVID-19 and artificial intelligence: trends and lessons

Ho Won Jang, Yang Liu, Youngeun Kim, Yeong Jae Kim
1 citations
Science Editing
COVID-19 diagnosis using AI
0.40
article

Publications on COVID-19 and artificial intelligence: trends and lessons

Ho Won Jang, Yang Liu, Youngeun Kim, Yeong Jae Kim
article en
1 citations

Abstract

Purpose: This study investigates shifts in scientific research focus, particularly the decline in COVID-19-related research and the rapid growth of artificial intelligence (AI) publications.Methods: We analyzed publication data from the Web of Science, comparing yearly publication counts for COVID-19 and AI research. The study also tracked changes in the impact factors of leading journals like <i>Science</i> and <i>Nature</i>, alongside those of top AI journals over the past decade. Additionally, we reviewed the top 10 most cited articles in 2021 from <i>Science</i> and <i>Nature</i> and the most influential AI publications from the past five years according to Google Scholar. The impact trends of the top 100 AI journals in computer science were also explored.Results: The analysis reveals a noticeable decline in COVID-19 related publications as the pandemic urgency diminishes, contrasted with the continued rapid growth of AI research. Impact factors for prestigious journals have shifted, with AI journals increasingly dominating the academic landscape. The review of top-cited articles further emphasizes these trends.Conclusion: Our findings indicate a significant shift in research priorities, with AI emerging as a dominant field poised to address future challenges, reflecting the evolving focus of the scientific community.

Science EditingVol. 11(2)
Seoul National University (KR)
National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Good health and well-being
Openalex Percentile: Top 36%
COVID-19 diagnosis using AI
0.40
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Publications on COVID-19 and artificial intelligence: trends and lessons — Ho Won Jang, Yang Liu, et al. · Science Editing (2024) | TGRS Research Map | TGRS