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A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022)
BACKGROUND: Colorectal cancer (CRC) has the third-highest incidence and second-highest mortality rate of all cancers worldwide. Early diagnosis and screening of CRC have been the focus of research in this field. With the continuous development of artificial intelligence (AI) technology, AI has advan...
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/PMC9941644/ https://www.ncbi.nlm.nih.gov/pubmed/36824138 http://dx.doi.org/10.3389/fonc.2023.1077539 |
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author | Huang, Pan Feng, Zongfeng Shu, Xufeng Wu, Ahao Wang, Zhonghao Hu, Tengcheng Cao, Yi Tu, Yi Li, Zhengrong |
author_facet | Huang, Pan Feng, Zongfeng Shu, Xufeng Wu, Ahao Wang, Zhonghao Hu, Tengcheng Cao, Yi Tu, Yi Li, Zhengrong |
author_sort | Huang, Pan |
collection | PubMed |
description | BACKGROUND: Colorectal cancer (CRC) has the third-highest incidence and second-highest mortality rate of all cancers worldwide. Early diagnosis and screening of CRC have been the focus of research in this field. With the continuous development of artificial intelligence (AI) technology, AI has advantages in many aspects of CRC, such as adenoma screening, genetic testing, and prediction of tumor metastasis. OBJECTIVE: This study uses bibliometrics to analyze research in AI in CRC, summarize the field’s history and current status of research, and predict future research directions. METHOD: We searched the SCIE database for all literature on CRC and AI. The documents span the period 2002-2022. we used bibliometrics to analyze the data of these papers, such as authors, countries, institutions, and references. Co-authorship, co-citation, and co-occurrence analysis were the main methods of analysis. Citespace, VOSviewer, and SCImago Graphica were used to visualize the results. RESULT: This study selected 1,531 articles on AI in CRC. China has published a maximum number of 580 such articles in this field. The U.S. had the most quality publications, boasting an average citation per article of 46.13. Mori Y and Ding K were the two authors with the highest number of articles. Scientific Reports, Cancers, and Frontiers in Oncology are this field’s most widely published journals. Institutions from China occupy the top 9 positions among the most published institutions. We found that research on AI in this field mainly focuses on colonoscopy-assisted diagnosis, imaging histology, and pathology examination. CONCLUSION: AI in CRC is currently in the development stage with good prospects. AI is currently widely used in colonoscopy, imageomics, and pathology. However, the scope of AI applications is still limited, and there is a lack of inter-institutional collaboration. The pervasiveness of AI technology is the main direction of future housing development in this field. |
format | Online Article Text |
id | pubmed-9941644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99416442023-02-22 A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) Huang, Pan Feng, Zongfeng Shu, Xufeng Wu, Ahao Wang, Zhonghao Hu, Tengcheng Cao, Yi Tu, Yi Li, Zhengrong Front Oncol Oncology BACKGROUND: Colorectal cancer (CRC) has the third-highest incidence and second-highest mortality rate of all cancers worldwide. Early diagnosis and screening of CRC have been the focus of research in this field. With the continuous development of artificial intelligence (AI) technology, AI has advantages in many aspects of CRC, such as adenoma screening, genetic testing, and prediction of tumor metastasis. OBJECTIVE: This study uses bibliometrics to analyze research in AI in CRC, summarize the field’s history and current status of research, and predict future research directions. METHOD: We searched the SCIE database for all literature on CRC and AI. The documents span the period 2002-2022. we used bibliometrics to analyze the data of these papers, such as authors, countries, institutions, and references. Co-authorship, co-citation, and co-occurrence analysis were the main methods of analysis. Citespace, VOSviewer, and SCImago Graphica were used to visualize the results. RESULT: This study selected 1,531 articles on AI in CRC. China has published a maximum number of 580 such articles in this field. The U.S. had the most quality publications, boasting an average citation per article of 46.13. Mori Y and Ding K were the two authors with the highest number of articles. Scientific Reports, Cancers, and Frontiers in Oncology are this field’s most widely published journals. Institutions from China occupy the top 9 positions among the most published institutions. We found that research on AI in this field mainly focuses on colonoscopy-assisted diagnosis, imaging histology, and pathology examination. CONCLUSION: AI in CRC is currently in the development stage with good prospects. AI is currently widely used in colonoscopy, imageomics, and pathology. However, the scope of AI applications is still limited, and there is a lack of inter-institutional collaboration. The pervasiveness of AI technology is the main direction of future housing development in this field. Frontiers Media S.A. 2023-02-07 /pmc/articles/PMC9941644/ /pubmed/36824138 http://dx.doi.org/10.3389/fonc.2023.1077539 Text en Copyright © 2023 Huang, Feng, Shu, Wu, Wang, Hu, Cao, Tu and Li 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 | Oncology Huang, Pan Feng, Zongfeng Shu, Xufeng Wu, Ahao Wang, Zhonghao Hu, Tengcheng Cao, Yi Tu, Yi Li, Zhengrong A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title | A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title_full | A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title_fullStr | A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title_full_unstemmed | A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title_short | A bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
title_sort | bibliometric and visual analysis of publications on artificial intelligence in colorectal cancer (2002-2022) |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941644/ https://www.ncbi.nlm.nih.gov/pubmed/36824138 http://dx.doi.org/10.3389/fonc.2023.1077539 |
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