The application of artificial intelligence in stroke research: A bibliometric analysis

Yun Peng ^1,2, Zhen Zhao ^1,2, Yutong Rao ^1,2

⁰Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Digital Health +

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March 3, 2025

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Summary

Artificial intelligence (AI) in stroke research has grown significantly over 20 years. Future AI applications in stroke may focus on early prediction and diagnosis using machine learning and natural language processing.

Area Of Science

Neuroscience
Medical Informatics
Rehabilitation Technology

Background

Artificial intelligence (AI) is increasingly utilized in stroke prediction, diagnosis, evaluation, and rehabilitation.
A comprehensive quantitative and qualitative overview of AI in stroke research is currently lacking.

Purpose Of The Study

To conduct a bibliometric analysis of AI applications in stroke research over the past two decades.
To elucidate the research status and evolving hotspots in this field.

Main Methods

Bibliometric analysis of 4437 publications from the Web of Science Core Collection (2003-2023).
Analysis of publication trends, country/region cooperation, institution co-occurrence, and keyword co-occurrence using CiteSpace and VOSviewer.

Main Results

A consistent upward trend in annual publications was observed.
The USA leads in publications and top institutions. Key research themes include rehabilitation, machine learning, recovery, and upper limb function.
Emerging hotspots include machine learning, natural language processing, and atrial fibrillation prediction.

Conclusions

The USA is a leading contributor to AI in stroke research.
Future research is likely to emphasize AI-driven prediction and rapid diagnosis of stroke using machine learning, deep learning, and natural language processing.

Keywords:

Artificial intelligence bibliometric stroke