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
Rodrigo Yáñez-Sepúlveda, Boryi A. Becerra-Patiño, Felipe Montalva-Valenzuela, Rodrigo Olivares, Alejandra Uribe-Díaz, Eduardo Guzmán-Muñoz, Yeny Concha-Cisternas, Daniel Rojas-Valverde, José Francisco Tornero-Aguilera, Vicente Javier Clemente-Suárez, José Francisco López-Gil · 2026
Read 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 by Rodrigo Yáñez-Sepúlveda, Boryi A. Becerra-Patiño, Felipe Montalva-Valenzuela, Rodrigo Olivares, Alejandra Uribe-Díaz, Eduardo Guzmán-Muñoz, Yeny Concha-Cisternas, Daniel Rojas-Valverde, José Francisco Tornero-Aguilera, Vicente Javier Clemente-Suárez, José Francisco López-Gil (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13565000.txt.
Description
Yáñez-Sepúlveda and co-authors test a simple question with machine learning, in a 2026 study of high blood pressure in Chile. The data come from the Chilean National Health Survey of 2016-2017, with 5,516 people aged 15 and older. The team built models from 54 inputs, then asked whether three easy measures, age, sex, and waist-to-height ratio, could do nearly as well. Seventeen algorithms were compared under careful grouped validation.
Across seven scoring metrics, the twelve tuned models performed much alike, and none won on every measure. The best full model scored well on held-out data, yet the three simple measures approached its discrimination. The result matters for clinics with few resources, where a tape measure and basic facts may flag risk almost as well as a large lab panel.
Catalog record
| CREATOR | Rodrigo Yáñez-Sepúlveda, Boryi A. Becerra-Patiño, Felipe Montalva-Valenzuela, Rodrigo Olivares, Alejandra Uribe-Díaz, Eduardo Guzmán-Muñoz, Yeny Concha-Cisternas, Daniel Rojas-Valverde, José Francisco Tornero-Aguilera, Vicente Javier Clemente-Suárez, José Francisco López-Gil |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 57 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |