From theory to practice – assessing translation of physical fitness research in the emergency department through machine learning and natural language processing
Having access to publicly available clinical research and associated EHR data, including clinician notes and after-visit summaries, provided a unique opportunity to assess the adoption of clinical research in medical practice. This approach can be used for a variety of clinical conditions, and if assessed over time could measure implementation effectiveness of quality improvement strategies and clinical guidelines.
Authors
- Lindsey Spiegelman
- Don Brown
- Kristin Morrow (ORCID: https://orcid.org/0009-0006-9384-4385)
- Dan M. Cooper (ORCID: https://orcid.org/0000-0003-4022-0043)
- Kai Zheng (ORCID: https://orcid.org/0000-0003-4121-4948)
- Roy Almog (ORCID: https://orcid.org/0000-0002-6557-5599)
- Debajyoti Datta (ORCID: https://orcid.org/0000-0003-0581-6116)
Institutions
- University of California, Irvine (US)
- University of California System (US)
- UC Irvine Health (US)
- University of Virginia (US)
Publication Details
- Journal
- Journal of Clinical and Translational Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1017/cts.2025.10051
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31
Funders
- Georgia Clinical and Translational Science Alliance
- University of Cambridge
- National Institutes of Health
- National Center for Advancing Translational Sciences