Predicting 30-day readmission after heart failure hospitalization using interpretable machine learning: evidence from a 20-year population-based rural registry.
- DOI
- 10.1007/s11517-026-03657-2
- Published
- 2026 Sep 7
- Container
- Medical & biological engineering & computing
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s11517-026-03657-2,
title = {Predicting 30-day readmission after heart failure hospitalization using interpretable machine learning: evidence from a 20-year population-based rural registry.},
author = {Maese-Calvo J and Paredes-Calderón A and Nunez-Bayon M and Arévalo-Lorido JC and Mayoral-Testón N and Nevado-Nogales C and José Zaro-Bastanzuri M and González-Fernández R and Hernández-Rollán N and Corral-García J and Rico-Gallego JA and Fernández-Bergés D},
year = {2026},
journal = {Medical \& biological engineering \& computing},
doi = {10.1007/s11517-026-03657-2},
url = {https://doi.org/10.1007/s11517-026-03657-2}
}RIS
TY - JOUR TI - Predicting 30-day readmission after heart failure hospitalization using interpretable machine learning: evidence from a 20-year population-based rural registry. AU - Maese-Calvo J AU - Paredes-Calderón A AU - Nunez-Bayon M AU - Arévalo-Lorido JC AU - Mayoral-Testón N AU - Nevado-Nogales C AU - José Zaro-Bastanzuri M AU - González-Fernández R AU - Hernández-Rollán N AU - Corral-García J AU - Rico-Gallego JA AU - Fernández-Bergés D PY - 2026 JO - Medical & biological engineering & computing DO - 10.1007/s11517-026-03657-2 UR - https://doi.org/10.1007/s11517-026-03657-2 ER -
APA
J, M., A, P., M, N., JC, A., N, M., C, N., M, J. Z., R, G., N, H., J, C., JA, R., & D, F. (2026). Predicting 30-day readmission after heart failure hospitalization using interpretable machine learning: evidence from a 20-year population-based rural registry.. Medical & biological engineering & computing. https://doi.org/10.1007/s11517-026-03657-2
Source records
- pubmed · retrieved 2026-09-25T17:07:00.424Z