Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis
Abstract Background Interest in artificial intelligence (AI) research in anesthesia is growing rapidly. However, there is a lack of bibliometric analysis to measure and analyze global scientific publications in this field. The aim of this study was to identify the hotspots and trends in AI research...
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| Language: | English |
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BMC
2025-04-01
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| Series: | Perioperative Medicine |
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| Online Access: | https://doi.org/10.1186/s13741-025-00531-x |
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| author | Yi Ou Xiaoyi Hu Cong Luo Yajun Li |
| author_facet | Yi Ou Xiaoyi Hu Cong Luo Yajun Li |
| author_sort | Yi Ou |
| collection | DOAJ |
| description | Abstract Background Interest in artificial intelligence (AI) research in anesthesia is growing rapidly. However, there is a lack of bibliometric analysis to measure and analyze global scientific publications in this field. The aim of this study was to identify the hotspots and trends in AI research in anesthesia through bibliometric analysis. Methods English articles and reviews published from 2000 to 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. The extracted data were summarized and analyzed using Microsoft Excel, and bibliometric analysis were conducted with VOSviewer software. Results AI research literature in anesthesia has exhibited rapid growth in recent years. The United States leads in the number of publications and citations, with Stanford University as the most prolific institution. Hyung-Chul Lee is the author with the highest number of publications. The journal Anesthesiology is highly recognized and authoritative in this field. Recent keywords include "musculoskeletal pain", "precision medicine", "stratification", "images", "mean arterial pressure", " enhanced recovery after surgery", "frailty", "telehealth", "postoperative delirium" and "postoperative mortality" indicating hot topics in AI research in anesthesia. Conclusions Publications on AI research in the field of anesthesia have experienced rapid growth over the past two decades and are likely to continue increasing. Research areas such as depth of anesthesia (DOA) and drug infusion (including electroencephalography and deep learning), perioperative risk assessment and prediction (covering mean arterial pressure, frailty, postoperative delirium, and mortality), image classification and recognition (for applications such as ultrasound-guided nerve blocks, vascular access, and difficult airway assessment), and perioperative pain management (particularly musculoskeletal pain) have garnered significant attention. Additionally, topics such as precision medicine, enhanced recovery after surgery, and telehealth are emerging as new hotspots and future directions in this field. |
| format | Article |
| id | doaj-art-ad9539ade979489eb337cd4585e14bd3 |
| institution | OA Journals |
| issn | 2047-0525 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Perioperative Medicine |
| spelling | doaj-art-ad9539ade979489eb337cd4585e14bd32025-08-20T02:30:25ZengBMCPerioperative Medicine2047-05252025-04-0114111510.1186/s13741-025-00531-xGlobal trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysisYi Ou0Xiaoyi Hu1Cong Luo2Yajun Li3Department of Anesthesiology, Chengdu Sixth People’s HospitalNanjing Medical UniversityDepartment of Anesthesiology, Chengdu Sixth People’s HospitalDepartment of Anesthesiology, Chengdu Sixth People’s HospitalAbstract Background Interest in artificial intelligence (AI) research in anesthesia is growing rapidly. However, there is a lack of bibliometric analysis to measure and analyze global scientific publications in this field. The aim of this study was to identify the hotspots and trends in AI research in anesthesia through bibliometric analysis. Methods English articles and reviews published from 2000 to 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. The extracted data were summarized and analyzed using Microsoft Excel, and bibliometric analysis were conducted with VOSviewer software. Results AI research literature in anesthesia has exhibited rapid growth in recent years. The United States leads in the number of publications and citations, with Stanford University as the most prolific institution. Hyung-Chul Lee is the author with the highest number of publications. The journal Anesthesiology is highly recognized and authoritative in this field. Recent keywords include "musculoskeletal pain", "precision medicine", "stratification", "images", "mean arterial pressure", " enhanced recovery after surgery", "frailty", "telehealth", "postoperative delirium" and "postoperative mortality" indicating hot topics in AI research in anesthesia. Conclusions Publications on AI research in the field of anesthesia have experienced rapid growth over the past two decades and are likely to continue increasing. Research areas such as depth of anesthesia (DOA) and drug infusion (including electroencephalography and deep learning), perioperative risk assessment and prediction (covering mean arterial pressure, frailty, postoperative delirium, and mortality), image classification and recognition (for applications such as ultrasound-guided nerve blocks, vascular access, and difficult airway assessment), and perioperative pain management (particularly musculoskeletal pain) have garnered significant attention. Additionally, topics such as precision medicine, enhanced recovery after surgery, and telehealth are emerging as new hotspots and future directions in this field.https://doi.org/10.1186/s13741-025-00531-xArtificial intelligenceAnesthesiaBibliometricsVOSviewer |
| spellingShingle | Yi Ou Xiaoyi Hu Cong Luo Yajun Li Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis Perioperative Medicine Artificial intelligence Anesthesia Bibliometrics VOSviewer |
| title | Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis |
| title_full | Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis |
| title_fullStr | Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis |
| title_full_unstemmed | Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis |
| title_short | Global trends in artificial intelligence research in anesthesia from 2000 to 2023: a bibliometric analysis |
| title_sort | global trends in artificial intelligence research in anesthesia from 2000 to 2023 a bibliometric analysis |
| topic | Artificial intelligence Anesthesia Bibliometrics VOSviewer |
| url | https://doi.org/10.1186/s13741-025-00531-x |
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