Artificial intelligence applied to diabetes complications: a bibliometric analysis
Background and aimsArtificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2025.1455341/full |
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| author | Yukun Tao Jinzheng Hou Guangxin Zhou Da Zhang |
| author_facet | Yukun Tao Jinzheng Hou Guangxin Zhou Da Zhang |
| author_sort | Yukun Tao |
| collection | DOAJ |
| description | Background and aimsArtificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots.MethodologyOn April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed. Based on bibliometric tools such as CiteSpace, Vosviewer and bibliometix, we construct knowledge maps to visualize literature information, including annual scientific production, authors, countries, institutions, journals, keywords and research hotspots.ResultsA total of 935 articles meeting the criteria were collected and analyzed. The number of annual publications showed an upward trend. Raman, Rajiv published the most articles, and Webster, Dale R had the highest collaboration frequency. The United States, China, and India were the most productive countries. Scientific Reports was the journal with the most publications. The three most frequent diabetes complications were diabetic retinopathy, diabetic nephropathy, and diabetic foot. Machine learning, diabetic retinopathy, screening, deep learning, and diabetic foot are still being researched in 2024.ConclusionGlobal AI research on diabetes complications is expected to increase further. The investigation of AI in diabetic retinopathy and diabetic foot will be the focus of research in the future. |
| format | Article |
| id | doaj-art-2adb6c58ee314c99b09689add6327038 |
| institution | Kabale University |
| issn | 2624-8212 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj-art-2adb6c58ee314c99b09689add63270382025-01-31T12:32:05ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122025-01-01810.3389/frai.2025.14553411455341Artificial intelligence applied to diabetes complications: a bibliometric analysisYukun TaoJinzheng HouGuangxin ZhouDa ZhangBackground and aimsArtificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots.MethodologyOn April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed. Based on bibliometric tools such as CiteSpace, Vosviewer and bibliometix, we construct knowledge maps to visualize literature information, including annual scientific production, authors, countries, institutions, journals, keywords and research hotspots.ResultsA total of 935 articles meeting the criteria were collected and analyzed. The number of annual publications showed an upward trend. Raman, Rajiv published the most articles, and Webster, Dale R had the highest collaboration frequency. The United States, China, and India were the most productive countries. Scientific Reports was the journal with the most publications. The three most frequent diabetes complications were diabetic retinopathy, diabetic nephropathy, and diabetic foot. Machine learning, diabetic retinopathy, screening, deep learning, and diabetic foot are still being researched in 2024.ConclusionGlobal AI research on diabetes complications is expected to increase further. The investigation of AI in diabetic retinopathy and diabetic foot will be the focus of research in the future.https://www.frontiersin.org/articles/10.3389/frai.2025.1455341/fullartificial intelligencediabetes complicationsbibliometric analysisdeep learningmachine learning |
| spellingShingle | Yukun Tao Jinzheng Hou Guangxin Zhou Da Zhang Artificial intelligence applied to diabetes complications: a bibliometric analysis Frontiers in Artificial Intelligence artificial intelligence diabetes complications bibliometric analysis deep learning machine learning |
| title | Artificial intelligence applied to diabetes complications: a bibliometric analysis |
| title_full | Artificial intelligence applied to diabetes complications: a bibliometric analysis |
| title_fullStr | Artificial intelligence applied to diabetes complications: a bibliometric analysis |
| title_full_unstemmed | Artificial intelligence applied to diabetes complications: a bibliometric analysis |
| title_short | Artificial intelligence applied to diabetes complications: a bibliometric analysis |
| title_sort | artificial intelligence applied to diabetes complications a bibliometric analysis |
| topic | artificial intelligence diabetes complications bibliometric analysis deep learning machine learning |
| url | https://www.frontiersin.org/articles/10.3389/frai.2025.1455341/full |
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