ArticleJournal of multidisciplinary healthcare2025
Research Hotspots and Prospects of Artificial Intelligence in Cardiovascular Disease: A Bibliometric Analysis.
Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To analyze the current status, research hotspots, and trends in the application of artificial intelligence (AI) in cardiovascular disease (CVD) using bibliometric methods, providing a reference for future research. Methods: A systematic search was conducted in the WoSCC for relevant literature published from database inception to March 5, 2025. VOSviewer v.1.6.20 was used for co-occurrence analysis of institutions (≥10 publications) and authors (≥5 publications), and Scimago Graphica V1.0.25 was used to visualize collaboration networks among countries/regions. CiteSpace 6.3.R1 was employed for institutional co-occurrence analysis (≥5 publications), keyword co-occurrence, and clustering analysis. Results: A total of 1738 relevant articles were included, with a gradual increase in annual publications, especially after 2018. The United States led in both publication volume and total citations. Harvard Medical School was the most prolific institution. Saba, Luca, and Suri, Jasjit S. were the most productive authors. 《 Conclusion: Research on AI in the field of CVD is still in a stage of rapid development. Currently, the hotspots in this field focus on the application of AI in CVD diagnosis and classification, the application of AI in CVD risk prediction, and the precise utilization of AI in CVD imaging. How to develop explainable AI models is a hot topic of research in the coming period.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.