Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy
Background In recent years, artificial intelligence (AI) has shown rapid development in the medical field, and its application in diabetic retinopathy (DR) has been expanding. Objective To summarize the application of AI in DR through bibliometric analysis and elucidate the current status, hot spots...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Chinese General Practice Publishing House Co., Ltd
2023-05-01
|
| Series: | Zhongguo quanke yixue |
| Subjects: | |
| Online Access: | https://www.chinagp.net/fileup/1007-9572/PDF/zx20220851.pdf |
| _version_ | 1797216726185672704 |
|---|---|
| author | LIU Chun, JIAN Wenyuan, DUAN Junguo |
| author_facet | LIU Chun, JIAN Wenyuan, DUAN Junguo |
| author_sort | LIU Chun, JIAN Wenyuan, DUAN Junguo |
| collection | DOAJ |
| description | Background In recent years, artificial intelligence (AI) has shown rapid development in the medical field, and its application in diabetic retinopathy (DR) has been expanding. Objective To summarize the application of AI in DR through bibliometric analysis and elucidate the current status, hot spots and emerging trends of AI-related research in DR, with a view to providing ideas for future research. Methods The research was performed on the Web of Science database for the researches related to AI applications in DR from inception to 2022-11-04 and used CiteSpace software to conduct bibliometric analysis of the number of articles, countries, institutions, authors, co-citation and keywords in the literature. Results A total of 1 770 papers were obtained, with an overall increasing trend in the number of publications and a peak of 402 papers in 2021. China was the top country in terms of the number of publications (440), and the UK was the country with the highest intermediary centrality (0.26). A total of 436 institutions were included in the institutional collaboration network mapping, represented by Sun Yat-sen University and Capital Medical University. A total of 601 authors were included in the author collaboration network mapping, represented by JIA Y L and HWANG T. Three highly cited authors, GULSHAN V, ABRàMOFF M D and TING D W, have made important contributions to the field. Ophthalmology, Invest Ophth Vis Sci and Ieee T Med Imaging are the three most influential journals in the field of AI applied to DR. The research hot spots were mainly focused on lesion segmentation and DR diagnosis. The future research trends may be efficacy prediction of diabetic macular edema as a complication of DR, disease management and improvement of AI algorithm performance. Conclusion Researchers can refer to the research hot spots and trends shown by this bibliometric analysis, focusing on AI in DR diagnosis, disease management and improvement of AI algorithm performance. |
| first_indexed | 2024-04-24T11:50:32Z |
| format | Article |
| id | doaj.art-c2054f2b13b8488585d0993ac755a8bf |
| institution | Directory Open Access Journal |
| issn | 1007-9572 |
| language | zho |
| last_indexed | 2024-04-24T11:50:32Z |
| publishDate | 2023-05-01 |
| publisher | Chinese General Practice Publishing House Co., Ltd |
| record_format | Article |
| series | Zhongguo quanke yixue |
| spelling | doaj.art-c2054f2b13b8488585d0993ac755a8bf2024-04-09T07:53:24ZzhoChinese General Practice Publishing House Co., LtdZhongguo quanke yixue1007-95722023-05-0126151847185610.12114/j.issn.1007-9572.2022.0851Bibliometric Analysis of Artificial Intelligence in Diabetic RetinopathyLIU Chun, JIAN Wenyuan, DUAN Junguo01. Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China;2. Ineye Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu 610084, China;3. Key Laboratory of Sichuan Province Ophthalmopathy Prevention & Cure and Visual Function Protection, Chengdu 610075, ChinaBackground In recent years, artificial intelligence (AI) has shown rapid development in the medical field, and its application in diabetic retinopathy (DR) has been expanding. Objective To summarize the application of AI in DR through bibliometric analysis and elucidate the current status, hot spots and emerging trends of AI-related research in DR, with a view to providing ideas for future research. Methods The research was performed on the Web of Science database for the researches related to AI applications in DR from inception to 2022-11-04 and used CiteSpace software to conduct bibliometric analysis of the number of articles, countries, institutions, authors, co-citation and keywords in the literature. Results A total of 1 770 papers were obtained, with an overall increasing trend in the number of publications and a peak of 402 papers in 2021. China was the top country in terms of the number of publications (440), and the UK was the country with the highest intermediary centrality (0.26). A total of 436 institutions were included in the institutional collaboration network mapping, represented by Sun Yat-sen University and Capital Medical University. A total of 601 authors were included in the author collaboration network mapping, represented by JIA Y L and HWANG T. Three highly cited authors, GULSHAN V, ABRàMOFF M D and TING D W, have made important contributions to the field. Ophthalmology, Invest Ophth Vis Sci and Ieee T Med Imaging are the three most influential journals in the field of AI applied to DR. The research hot spots were mainly focused on lesion segmentation and DR diagnosis. The future research trends may be efficacy prediction of diabetic macular edema as a complication of DR, disease management and improvement of AI algorithm performance. Conclusion Researchers can refer to the research hot spots and trends shown by this bibliometric analysis, focusing on AI in DR diagnosis, disease management and improvement of AI algorithm performance.https://www.chinagp.net/fileup/1007-9572/PDF/zx20220851.pdfdiabetic retinopathy|artificial intelligence|citespace|bibliometric analysis|visualization |
| spellingShingle | LIU Chun, JIAN Wenyuan, DUAN Junguo Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy Zhongguo quanke yixue diabetic retinopathy|artificial intelligence|citespace|bibliometric analysis|visualization |
| title | Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy |
| title_full | Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy |
| title_fullStr | Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy |
| title_full_unstemmed | Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy |
| title_short | Bibliometric Analysis of Artificial Intelligence in Diabetic Retinopathy |
| title_sort | bibliometric analysis of artificial intelligence in diabetic retinopathy |
| topic | diabetic retinopathy|artificial intelligence|citespace|bibliometric analysis|visualization |
| url | https://www.chinagp.net/fileup/1007-9572/PDF/zx20220851.pdf |
| work_keys_str_mv | AT liuchunjianwenyuanduanjunguo bibliometricanalysisofartificialintelligenceindiabeticretinopathy |