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Review
. 2025 May 7:12:1497822.
doi: 10.3389/fcvm.2025.1497822. eCollection 2025.

Data source and utilization of artificial intelligence technologies in vascular surgery-a scoping review

Katarzyna Powezka  1   2   3 , Karin Slater  2 , David Brind  2 , Michael Wall  2   3 , Georgios Gkoutos  2 , Maciej Juszczak  1   2
Affiliations
Review

Data source and utilization of artificial intelligence technologies in vascular surgery-a scoping review

Katarzyna Powezka et al. Front Cardiovasc Med. .

Abstract

Objective: The goals of this scoping review were to determine the source of data used to develop AI-based algorithms with emphasis on natural language processing, establish their application in different areas of vascular surgery and identify a target audience of published journals.

Materials and methods: A literature search was carried out using established database from January 1996 to March 2023.

Results: 342 peer-reviewed articles met the eligibility criteria. NLP algorithms were described in 34 papers, while 115 and 193 papers focused on machine learning (ML) and deep learning (DL), respectively. The AI-based algorithms found widest application in research related to aorta (126 articles), carotid disease (85), and peripheral arterial disease (65). Image-based data were utilised in 216 articles, while 153 and 85 papers relied on medical records, and clinical parameters. The AI algorithms were used for predictive modelling (123 papers), medical image segmentation (118), and to aid identification, detection, and diagnosis (103).

Discussion: Applications of Artificial Intelligence (AI) are gaining traction in healthcare, including vascular surgery. While most healthcare data is in the form of narrative text or audio recordings, natural language processing (NLP) offers the ability to extract information from unstructured medical records. This can be used to develop more accurate risk prediction models, support shared-decision model, and identify patients for trials to improve recruitment.

Conclusion: Utilisation of different data sources and AI technologies depends on the purpose of the undertaken research. Despite the abundance of available of textual data, the NLP is disproportionally underutilised AI sub-domain in vascular surgery.

Keywords: AI applications; artificial intelligence; identification; natural language processing; predictive modelling; source of data; vascular surgery.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The search queries employed to screen the PUBMED, EMBASE and google scholar database.
Figure 2
Figure 2
PRISMA diagram from initial literature search to final number of studies included in the analysis.
Figure 3
Figure 3
Input data for AI algorithms creation in vascular surgery.
Figure 4
Figure 4
Application of AI-based algorithms in vascular conditions.
See this image and copyright information in PMC

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