ArticleDiagnostics (Basel, Switzerland)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.
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 and 1 more
Abstract read
In one paragraphArticle in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from itWhat it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
11 authors.
Rodrigo Yáñez-SepúlvedaFaculty of Education and Humanities, Universidad Andrés Bello, Vina del Mar 2520000, Chile.ORCID 0000-0002-9311-6576 Boryi A Becerra-PatiñoFacultad de Educación Física, Universidad Pedagógica Nacional, Bogota 480100, Colombia.ORCID 0000-0002-9581-5071 Felipe Montalva-ValenzuelaEscuela de Entrenador en Actividad Física y Deporte, Facultad de Ciencias Humanas, Universidad Bernardo O'Higgins, Santiago 8370040, Chile.ORCID 0000-0003-0004-3089 Rodrigo OlivaresEscuela de Ingeniería Informática, Universidad de Valparaíso, Valparaiso 2340000, Chile.ORCID 0000-0003-0582-954X Alejandra Uribe-DíazFaculty of Health Sciences, Universidad Tecnológica Atlántico Mediterráneo (UTAMED), 29590 Malaga, Spain.
Eduardo Guzmán-MuñozEscuela de Kinesiología, Facultad de Salud, Universidad Santo Tomás, Talca 3460000, Chile.ORCID 0000-0001-7001-9004 Yeny Concha-CisternasEscuela de Kinesiología, Facultad de Salud, Universidad Santo Tomás, Talca 3460000, Chile.ORCID 0000-0001-7013-3894 Daniel Rojas-ValverdeCentro de Investigación, Desarrollo e Innovación en Salud y Deporte (CIDISAD), Escuela Ciencias del Movimiento Humano y Calidad de Vida (CIEMHCAVI), Universidad Nacional de Costa Rica, Heredia 863000, Costa Rica.ORCID 0000-0002-0717-8827 José Francisco Tornero-AguileraDepartment of Sport Sciences, Faculty of Sport and Health Sciences, Fit Generation Research Institute, AD500 Andorra la Vella, Andorra.
Vicente Javier Clemente-SuárezDepartment of Sport Sciences, Faculty of Sport and Health Sciences, Fit Generation Research Institute, AD500 Andorra la Vella, Andorra.ORCID 0000-0002-2397-2801 José Francisco López-GilSchool of Medicine, Universidad Espíritu Santo, Samborondon 092301, Ecuador.ORCID 0000-0002-7412-7624 Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
PubMed holds no abstract for this paper.
Indexed as
Chilecomplex survey designexplainable artificial intelligencehealth surveyhypertensionmachine learningmodel parsimonyprediction modelSHapley Additive exPlanations
Identifiers
PMID42739273
PMCPMC13565000
What Socratic holds
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