College of Nursing
Seo-Yoon Lee Research Group
Led by Seo-Yoon Lee · Biobehavioral Nursing Science
What we study
The Lee Lab studies how healthcare data and AI can improve nursing care by analyzing electronic health records to reduce workload and optimize patient outcomes. Their work focuses on making nursing costs visible and using data-driven tools to support safer care.
What working here is like
- Computational
- Coding required
- Project
- 1
- Papers
- 5
Current projects
Estimating patient-level cost of nursing care
Using integrated EHR and staffing data to reveal nursing costs and their links to patient and nurse characteristics.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- Patient‑level nursing cost analysis and cost drivers in acute care: A retrospective longitudinal study
2026 · Nursing Outlook
Analyzes nursing costs per patient and identifies factors that drive those costs.
- Natural Language Processing for Substance Use Disorder Information Extraction: A Systematic Literature Review
2026 · Current Addiction Reports
Reviews how natural language processing is used to extract information about substance use disorders.
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- Ambient AI’s Value for Nursing: Will “Saving Time” Be a “Staffing Trap”?
2026 · Applied Clinical Informatics
- Constructing the Nursing Value Model Using Readily Available Datasets
2025 · CIN Computers Informatics Nursing
Describes how to build a model to measure nursing care value using available healthcare data.
- Religious Leaders’ Experience of Advance Care Planning and Death-Related Discussions With Korean Americans: A Qualitative Study Identifying Obstacles and Strategies
2025 · Journal of Hospice and Palliative Nursing
Explores challenges and strategies religious leaders face when discussing advance care planning with Korean Americans.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
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