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The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis
BACKGROUND: With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate can...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921533/ https://www.ncbi.nlm.nih.gov/pubmed/35299747 http://dx.doi.org/10.3389/fonc.2022.843735 |
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author | Shen, Zefeng Wu, Haiyang Chen, Zeshi Hu, Jintao Pan, Jiexin Kong, Jianqiu Lin, Tianxin |
author_facet | Shen, Zefeng Wu, Haiyang Chen, Zeshi Hu, Jintao Pan, Jiexin Kong, Jianqiu Lin, Tianxin |
author_sort | Shen, Zefeng |
collection | PubMed |
description | BACKGROUND: With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer. OBJECTIVE: This study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots. METHODS: The articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field. RESULTS: A total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: “Diagnosis and Prediction AI-related study”, “Non-surgery AI-related study”, and “Surgery AI-related study”. Meanwhile, the current research hotspots were “deep learning” and “multiparametric MRI”. CONCLUSIONS: Artificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years. |
format | Online Article Text |
id | pubmed-8921533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89215332022-03-16 The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis Shen, Zefeng Wu, Haiyang Chen, Zeshi Hu, Jintao Pan, Jiexin Kong, Jianqiu Lin, Tianxin Front Oncol Oncology BACKGROUND: With the rapid development of technology, artificial intelligence (AI) has been widely used in the diagnosis and prognosis prediction of a variety of diseases, including prostate cancer. Facts have proved that AI has broad prospects in the accurate diagnosis and treatment of prostate cancer. OBJECTIVE: This study mainly summarizes the research on the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores possible future research hotspots. METHODS: The articles and reviews regarding application of AI in prostate cancer between 1999 and 2020 were selected from Web of Science Core Collection on August 23, 2021. Microsoft Excel 2019 and GraphPad Prism 8 were applied to analyze the targeted variables. VOSviewer (version 1.6.16), Citespace (version 5.8.R2), and a widely used online bibliometric platform were used to conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field. RESULTS: A total of 2,749 articles were selected in this study. AI-related research on prostate cancer increased exponentially in recent years, of which the USA was the most productive country with 1,342 publications, and had close cooperation with many countries. The most productive institution and researcher were the Henry Ford Health System and Tewari. However, the cooperation among most institutions or researchers was not close even if the high research outputs. The result of keyword analysis could divide all studies into three clusters: “Diagnosis and Prediction AI-related study”, “Non-surgery AI-related study”, and “Surgery AI-related study”. Meanwhile, the current research hotspots were “deep learning” and “multiparametric MRI”. CONCLUSIONS: Artificial intelligence has broad application prospects in prostate cancer, and a growing number of scholars are devoted to AI-related research on prostate cancer. Meanwhile, the cooperation among various countries and institutions needs to be strengthened in the future. It can be projected that noninvasive diagnosis and accurate minimally invasive treatment through deep learning technology will still be the research focus in the next few years. Frontiers Media S.A. 2022-03-01 /pmc/articles/PMC8921533/ /pubmed/35299747 http://dx.doi.org/10.3389/fonc.2022.843735 Text en Copyright © 2022 Shen, Wu, Chen, Hu, Pan, Kong and Lin 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 Shen, Zefeng Wu, Haiyang Chen, Zeshi Hu, Jintao Pan, Jiexin Kong, Jianqiu Lin, Tianxin The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title | The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title_full | The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title_fullStr | The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title_full_unstemmed | The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title_short | The Global Research of Artificial Intelligence on Prostate Cancer: A 22-Year Bibliometric Analysis |
title_sort | global research of artificial intelligence on prostate cancer: a 22-year bibliometric analysis |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921533/ https://www.ncbi.nlm.nih.gov/pubmed/35299747 http://dx.doi.org/10.3389/fonc.2022.843735 |
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