Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study
BackgroundPatients with retinal diseases may exhibit serious complications that cause severe visual impairment owing to a lack of awareness of retinal diseases and limited medical resources. Understanding how artificial intelligence (AI) is used to make predictions and perfor...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2022-06-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/6/e37532 |
| _version_ | 1797734979326705664 |
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| author | Junqiang Zhao Yi Lu Yong Qian Yuxin Luo Weihua Yang |
| author_facet | Junqiang Zhao Yi Lu Yong Qian Yuxin Luo Weihua Yang |
| author_sort | Junqiang Zhao |
| collection | DOAJ |
| description |
BackgroundPatients with retinal diseases may exhibit serious complications that cause severe visual impairment owing to a lack of awareness of retinal diseases and limited medical resources. Understanding how artificial intelligence (AI) is used to make predictions and perform relevant analyses is a very active area of research on retinal diseases. In this study, the relevant Science Citation Index (SCI) literature on the AI of retinal diseases published from 2012 to 2021 was integrated and analyzed.
ObjectiveThe aim of this study was to gain insights into the overall application of AI technology to the research of retinal diseases from set time and space dimensions.
MethodsCitation data downloaded from the Web of Science Core Collection database for AI in retinal disease publications from January 1, 2012, to December 31, 2021, were considered for this analysis. Information retrieval was analyzed using the online analysis platforms of literature metrology: Bibliometrc, CiteSpace V, and VOSviewer.
ResultsA total of 197 institutions from 86 countries contributed to relevant publications; China had the largest number and researchers from University College London had the highest H-index. The reference clusters of SCI papers were clustered into 12 categories. “Deep learning” was the cluster with the widest range of cocited references. The burst keywords represented the research frontiers in 2018-2021, which were “eye disease” and “enhancement.”
ConclusionsThis study provides a systematic analysis method on the literature regarding AI in retinal diseases. Bibliometric analysis enabled obtaining results that were objective and comprehensive. In the future, high-quality retinal image–forming AI technology with strong stability and clinical applicability will continue to be encouraged. |
| first_indexed | 2024-03-12T12:52:19Z |
| format | Article |
| id | doaj.art-378c105fed214f3fbe278637ef5bf490 |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:52:19Z |
| publishDate | 2022-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-378c105fed214f3fbe278637ef5bf4902023-08-28T22:17:47ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-06-01246e3753210.2196/37532Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization StudyJunqiang Zhaohttps://orcid.org/0000-0002-0250-4689Yi Luhttps://orcid.org/0000-0001-9182-853XYong Qianhttps://orcid.org/0000-0002-3944-4499Yuxin Luohttps://orcid.org/0000-0001-5348-0712Weihua Yanghttps://orcid.org/0000-0002-7629-0193 BackgroundPatients with retinal diseases may exhibit serious complications that cause severe visual impairment owing to a lack of awareness of retinal diseases and limited medical resources. Understanding how artificial intelligence (AI) is used to make predictions and perform relevant analyses is a very active area of research on retinal diseases. In this study, the relevant Science Citation Index (SCI) literature on the AI of retinal diseases published from 2012 to 2021 was integrated and analyzed. ObjectiveThe aim of this study was to gain insights into the overall application of AI technology to the research of retinal diseases from set time and space dimensions. MethodsCitation data downloaded from the Web of Science Core Collection database for AI in retinal disease publications from January 1, 2012, to December 31, 2021, were considered for this analysis. Information retrieval was analyzed using the online analysis platforms of literature metrology: Bibliometrc, CiteSpace V, and VOSviewer. ResultsA total of 197 institutions from 86 countries contributed to relevant publications; China had the largest number and researchers from University College London had the highest H-index. The reference clusters of SCI papers were clustered into 12 categories. “Deep learning” was the cluster with the widest range of cocited references. The burst keywords represented the research frontiers in 2018-2021, which were “eye disease” and “enhancement.” ConclusionsThis study provides a systematic analysis method on the literature regarding AI in retinal diseases. Bibliometric analysis enabled obtaining results that were objective and comprehensive. In the future, high-quality retinal image–forming AI technology with strong stability and clinical applicability will continue to be encouraged.https://www.jmir.org/2022/6/e37532 |
| spellingShingle | Junqiang Zhao Yi Lu Yong Qian Yuxin Luo Weihua Yang Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study Journal of Medical Internet Research |
| title | Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study |
| title_full | Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study |
| title_fullStr | Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study |
| title_full_unstemmed | Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study |
| title_short | Emerging Trends and Research Foci in Artificial Intelligence for Retinal Diseases: Bibliometric and Visualization Study |
| title_sort | emerging trends and research foci in artificial intelligence for retinal diseases bibliometric and visualization study |
| url | https://www.jmir.org/2022/6/e37532 |
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