Integrating administrative health data and machine learning to predict ALS onset
Machine Learning models, particularly stacked approaches, show promising results in predicting ALS diagnoses using administrative health data. Continued research is necessary to improve detection strategies and support their integration into healthcare systems.
Authors
- Toni Mora (ORCID: https://orcid.org/0000-0002-2686-5307)
- David Roche (ORCID: https://orcid.org/0000-0002-7524-4590)
- Mónica Povedano (ORCID: https://orcid.org/0000-0001-5146-6183)
- Alejandro Caravaca Puchades
- Pol Andrés Benito
Institutions
- Bellvitge University Hospital (ES)
- Universitat Internacional de Catalunya (ES)
- Institut d'Investigació Biomédica de Bellvitge (ES)
Publication Details
- Journal
- Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration
- Published
- 2025-12-05
- DOI
- https://doi.org/10.1080/21678421.2025.2596691
- Primary Topic
- Amyotrophic Lateral Sclerosis Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00