Accessing Data in Health AI Research: Challenges, Insights & Recommendations
Description
The AI for Multiple Long-Term Conditions Research Support Facility (AIM RSF), a collaborative initiative led by The Alan Turing Institute in partnership with Swansea University, the University of Edinburgh and the University of Oxford, oversees eight research consortia across the UK to support and drive culture change in Multiple Long-Term Condition (MLTC) research. By connecting researchers, healthcare professionals, and patients, AIM RSF has reshaped our understanding of MLTCs.
The initiative focuses on five key areas: building robust infrastructure, improving data accessibility, creating a connected research community, engaging with the public, and ensuring lasting impact.
As we approach April 2025, marking the conclusion of this phase of the AIM RSF, we reflect on our achievements and the foundation we've laid for future advancements in MLTC research. This case study, the first in a series of three, shares our journey and offers insights and recommendations for those involved in health data research and AI.
AIM RSF is funded by the NIHR [Artificial Intelligence for Multiple Long-Term Conditions (AIM) programme (NIHR202647). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
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CS1 Accessing Data in Health AI Research- Challenges, Insights & Recommendations.pdf
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(15.9 MB)
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