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Bibliometric Analysis on Artificial Intelligence and Machine Learning in Vascular Surgery

Published:July 04, 2022DOI:https://doi.org/10.1016/j.avsg.2022.06.002
Bibliometric Analysis on Artificial Intelligence and Machine Learning in Vascular Surgery
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      Artificial Intelligence (AI) and Machine Learning (ML) have brought new insights in vascular diseases, as evidenced by an increasing number of published articles demonstrating their interest to improve diagnosis, build predictive models, assess the prognosis of patients, propose new devices and develop aid-decision support system with personalized therapeutic approach.
      • Li B.
      • Feridooni T.
      • Cuen-Ojeda C.
      • et al.
      Machine learning in vascular surgery: a systematic review and critical appraisal.
      NPJ Digit Med. 2022; 5: 7
      ,
      • Raffort J.
      • Adam C.
      • Carrier M.
      • et al.
      Fundamentals in artificial intelligence for vascular surgeons.
      Ann Vasc Surg. 2020; 65: 254-260
      Several reviews summarized the applications of AI in vascular diseases and mainly focused on aortic
      • Raffort J.
      • Adam C.
      • Carrier M.
      • et al.
      Artificial intelligence in abdominal aortic aneurysm.
      J Vasc Surg. 2020; 72: 321-333.e1
      ,
      • Hahn L.D.
      • Baeumler K.
      • Hsiao A.
      Artificial intelligence and machine learning in aortic disease.
      Curr Opin Cardiol. 2021; 36: 695-703
      and peripheral artery disease.
      • Flores A.M.
      • Demsas F.
      • Leeper N.J.
      • et al.
      Leveraging machine learning and artificial intelligence to improve peripheral artery disease detection, treatment, and outcomes.
      Circ Res. 2021; 128: 1833-1850
      However, bibliometric analysis investigating major topics, main AI techniques, contributors, journals, and context of research have been so far less reported.
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      References

        • Li B.
        • Feridooni T.
        • Cuen-Ojeda C.
        • et al.
        Machine learning in vascular surgery: a systematic review and critical appraisal.
        NPJ Digit Med. 2022; 5: 7
        View in Article
        • Raffort J.
        • Adam C.
        • Carrier M.
        • et al.
        Fundamentals in artificial intelligence for vascular surgeons.
        Ann Vasc Surg. 2020; 65: 254-260
        View in Article
        • Raffort J.
        • Adam C.
        • Carrier M.
        • et al.
        Artificial intelligence in abdominal aortic aneurysm.
        J Vasc Surg. 2020; 72: 321-333.e1
        View in Article
        • Hahn L.D.
        • Baeumler K.
        • Hsiao A.
        Artificial intelligence and machine learning in aortic disease.
        Curr Opin Cardiol. 2021; 36: 695-703
        View in Article
        • Flores A.M.
        • Demsas F.
        • Leeper N.J.
        • et al.
        Leveraging machine learning and artificial intelligence to improve peripheral artery disease detection, treatment, and outcomes.
        Circ Res. 2021; 128: 1833-1850
        View in Article
        • Lareyre F.
        • Le C.D.
        • Ballaith A.
        • et al.
        Applications of Artificial intelligence in non-cardiac vascular diseases: a bibliographic analysis.
        Angiology. 2022; 73: 606-614
        View in Article
        • Javidan A.P.
        • Li A.
        • Lee M.H.
        • et al.
        A systematic review and bibliometric analysis of applications of Artificial intelligence and machine learning in vascular surgery.
        Ann Vasc Surg. 2022; (Epub ahead of print.)
        View in Article
        • Lareyre F.
        • Adam C.
        • Carrier M.
        • et al.
        Artificial intelligence for education of vascular surgeons.
        Eur J Vasc Endovasc Surg. 2020; 59: 870-871
        View in Article

      Article Info

      Publication History

      Published online: July 04, 2022

      Publication stage

      In Press Journal Pre-Proof

      Footnotes

      Competing Interests: The authors declare no competing interest.

      Funding Sources: None declared.

      Identification

      DOI: https://doi.org/10.1016/j.avsg.2022.06.002

      Copyright

      © 2022 Elsevier Inc. All rights reserved.

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