Risk Stratification for In-Hospital Mortality in Alzheimer’s Disease Using Interpretable Regression and Explainable AI
Combining regression with explainable machine learning enables robust mortality risk stratification in hospitalized AD patients. Restricted models excluding end-of-life indicators provide actionable risk signals when such documentation is absent, while the full model may better support resource allocation and goals-of-care workflows.
Authors
- Tursun Alkam (ORCID: https://orcid.org/0009-0001-4150-8383)
- Ebrahim Tarshizi (ORCID: https://orcid.org/0009-0002-3769-3456)
- Andrew H Van Benschoten (ORCID: https://orcid.org/0000-0002-7944-6237)
Institutions
- University of San Diego (US)
- University of California San Diego (US)
Publication Details
- Journal
- Geriatrics
- Published
- 2026-02-24
- DOI
- https://doi.org/10.3390/geriatrics11020023
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agency for Healthcare Research and Quality