Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey
- DOI
- 10.3390/diagnostics16172843
- Published
- 2026-09-04
- Container
- Diagnostics
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/diagnostics16172843,
title = {Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey},
author = {Rodrigo Yáñez-Sepúlveda and Boryi A. Becerra-Patiño and Felipe Montalva-Valenzuela and Rodrigo Olivares and Alejandra Uribe-Díaz and Eduardo Guzmán-Muñoz and Yeny Concha-Cisternas and Daniel Rojas-Valverde and José Francisco Tornero-Aguilera and Vicente Javier Clemente-Suárez and José Francisco López-Gil},
year = {2026},
journal = {Diagnostics},
doi = {10.3390/diagnostics16172843},
url = {https://doi.org/10.3390/diagnostics16172843}
}RIS
TY - JOUR TI - Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey AU - Rodrigo Yáñez-Sepúlveda AU - Boryi A. Becerra-Patiño AU - Felipe Montalva-Valenzuela AU - Rodrigo Olivares AU - Alejandra Uribe-Díaz AU - Eduardo Guzmán-Muñoz AU - Yeny Concha-Cisternas AU - Daniel Rojas-Valverde AU - José Francisco Tornero-Aguilera AU - Vicente Javier Clemente-Suárez AU - José Francisco López-Gil PY - 2026 JO - Diagnostics DO - 10.3390/diagnostics16172843 UR - https://doi.org/10.3390/diagnostics16172843 ER -
APA
Yáñez-Sepúlveda, R., Becerra-Patiño, B. A., Montalva-Valenzuela, F., Olivares, R., Uribe-Díaz, A., Guzmán-Muñoz, E., Concha-Cisternas, Y., Rojas-Valverde, D., Tornero-Aguilera, J. F., Clemente-Suárez, V. J., & López-Gil, J. F. (2026). Age, Sex, and Waist-to-Height Ratio Approach the Discrimination of Fifty-Four Model Inputs for Prevalent Hypertension: An Explainable Machine Learning Analysis of the Chilean National Health Survey. Diagnostics. https://doi.org/10.3390/diagnostics16172843
Source records
- crossref · retrieved 2026-09-24T21:53:47.747Z