AI in Carotid Research: 1,220 Publications from 2000-2025

1,220 publications on artificial intelligence in carotid artery research were identified from a bibliometric analysis of Web of Science, Scopus, and PubMed. The dataset, created by Shi-Chao Zhu, includes network visualizations and structural analyses generated by CiteSpace to reveal thematic clusters. Publication volume shows an overall increasing trend, with China and the United States as the primary contributing countries.

Use Cases

• Analyze publication trends and growth in AI applications for carotid artery disease based on the 25-year time span
• Identify leading countries and institutions in this research field based on the contributor analysis
• Map evolving research themes like imaging omics and precision medicine based on the network visualizations
• Study the shift towards data-driven, multi-modal approaches in carotid research based on the described recent progress

Strengths

• Includes 1,220 relevant publications identified from three major academic databases
• Covers a 25-year time range from 2000 to 2025, allowing for trend analysis
• Analysis performed using established bibliometric tools like CiteSpace for network visualization

Limitations

• The dataset is a 16.8 KB DOCX file, suggesting limited raw data or a summary document
• Column-level documentation is absent; field semantics must be inferred after download
• Row count for any underlying bibliographic data is unknown, which may limit suitability assessment

Provenance

Source

Web of Science Core Collection, Scopus, and PubMed databases

Collection Method

Retrospective bibliometric analysis focusing on title/abstract/keyword queries

Time Range

2000 to 2025

Freshness

Last updated 2026-05-19 05:29:12

Geography

Global, with China and the United States noted as primary contributors