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An evaluation of funded National Institutes of Health grants in nursing science and artificial intelligence
Dillon J Dzikowicz1, Mehmed Aktas2, Jinjiao Wang1
1School of Nursing, University of Rochester, Rochester, NY.
Background:
The integration of artificial intelligence (AI) in nursing research holds significant potential. However, AI's development and deployment remains a crucial area of research.
Purpose:
This study aims to evaluate the type (e.g., R01, R21, and K08), topic, and cost of National Institutes of Health (NIH)-funded grants focusing on AI in nursing science from 2013 to 2023.
Methods:
Using the RePORTER database, we identified NIH-funded grants with keywords related to nursing and AI from 2013 to 2023. We used topic modeling on the project abstracts to uncover key themes.
Discussion:
We identified 370 NIH-funded AI and nursing-related grants, a 1,160% increase over time. Most NINR-funded projects were training-focused. Key themes included cognitive decline, inpatient predictive analytics, and chronic disease self-management.
Conclusion:
While AI-related funding is growing, nurse-led projects remain limited, highlighting the need for expanded nursing leadership in AI research. Strategic efforts are essential to support nurse scientists in shaping the future of AI-integrated nursing science.
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