Predicting first-time anaphylaxis in the elderly using stacked machine learning and population registers
This study demonstrates the potential of interpretable machine learning approaches to support the early identification of individuals at high risk of anaphylaxis. These tools can enhance clinical risk stratification and inform preventive strategies in routine practice.
Authors
- Toni Mora (ORCID: https://orcid.org/0000-0002-2686-5307)
- David Roche (ORCID: https://orcid.org/0000-0002-7524-4590)
- Rosa Muñoz‐Cano (ORCID: https://orcid.org/0000-0001-8566-8285)
Institutions
- Instituto de Salud Carlos III (ES)
- Universitat Internacional de Catalunya (ES)
- Hospital Clínic de Barcelona (ES)
- Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES)
Publication Details
- Journal
- Frontiers in Allergy
- Published
- 2025-11-06
- DOI
- https://doi.org/10.3389/falgy.2025.1655662
- Citations
- 2
- Primary Topic
- Food Allergy and Anaphylaxis Research
- Type
- article
- Field-Weighted Citation Impact
- 3.24
Funders
- Ministerio de Ciencia e Innovación
- Agencia Estatal de Investigación