Quantifying Innovation in Stroke: Large Language Model Bibliometric Analysis

Applying an LLM to publicly available patent and publication data provides a scalable way to quantify innovation in stroke. Pharmacological treatment appears to have entered a saturation phase, whereas AI methods, rehabilitation devices, and medical imaging remain in rapid growth, highlighting areas of greatest traction for future research and investment.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2026-01-20
DOI
https://doi.org/10.2196/70754
Primary Topic
Acute Ischemic Stroke Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying Innovation in Stroke: Large Language Model Bibliometric Analysis

Paul Bentley, Daniel Rueckert, Adam Marcus, Georgina Lockwood-Taylor
Journal of Medical Internet Research
Acute Ischemic Stroke Management
article

Quantifying Innovation in Stroke: Large Language Model Bibliometric Analysis

Paul Bentley, Daniel Rueckert, Adam Marcus, Georgina Lockwood-Taylor
article en

Abstract

Applying an LLM to publicly available patent and publication data provides a scalable way to quantify innovation in stroke. Pharmacological treatment appears to have entered a saturation phase, whereas AI methods, rehabilitation devices, and medical imaging remain in rapid growth, highlighting areas of greatest traction for future research and investment.

Journal of Medical Internet ResearchVol. 28
King's College London (GB), TUM Klinikum (DE), Imperial College London (GB), Technical University of Munich (DE)
Openalex Percentile: Top 84%
Acute Ischemic Stroke Management
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