SBDH-Reader: a large language model-powered method for extracting social and behavioral determinants of health from clinical notes
SBDH-Reader has the potential to serve as a scalable and effective method for collecting real-time, patient-level SBDH data to support clinical research and care.
Authors
- Guanghua Xiao (ORCID: https://orcid.org/0000-0001-9387-9883)
- Donghan M. Yang (ORCID: https://orcid.org/0000-0003-1935-0214)
- Jingwei Huang
- Wenqi Shi (ORCID: https://orcid.org/0000-0001-8972-7342)
- Matthew E. Dupre (ORCID: https://orcid.org/0000-0002-0976-4715)
- Ying Ding (ORCID: https://orcid.org/0000-0003-2567-2009)
- Ann Marie Návar (ORCID: https://orcid.org/0000-0002-6197-9860)
- Heba M. A. Khalil (ORCID: https://orcid.org/0000-0001-6008-2157)
- Zifan Gu (ORCID: https://orcid.org/0000-0002-8024-2629)
- Eric David Peterson (ORCID: https://orcid.org/0000-0002-5415-4721)
- Ismael Villanueva-Miranda
- Yang Xie
- Yujia Guo (ORCID: https://orcid.org/0000-0002-8850-1824)
- Ayesha Naeem (ORCID: https://orcid.org/0000-0002-2396-158X)
- A. A. Mohamed (ORCID: https://orcid.org/0009-0001-2426-1518)
- Li He
- Pui Man Chan
Institutions
- Duke University (US)
- Southwestern Medical Center (US)
- The University of Texas at Austin (US)
- The University of Texas Southwestern Medical Center (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2025-07-14
- DOI
- https://doi.org/10.1093/jamia/ocaf124
- Citations
- 3
- Primary Topic
- Food Security and Health in Diverse Populations
- Type
- article
- Field-Weighted Citation Impact
- 8.45
Funders
- Cancer Prevention and Research Institute of Texas
- National Institutes of Health