This paper is in the following e-collection/theme issue:

Outbreak and Pandemic Preparedness and Management (1743) JMIR Theme Issue: COVID-19 Special Issue (2461) Infectious Diseases (non-STD/STI) (1592) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Innovative Methods in Public Health and Surveillance (336) Statistical Methods for Surveillance and Population Health (158) Surveillance Systems (466) Validity, Reliability, and Bias (94)

Published on in Vol 8, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30032, first published .
Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique

Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique

Subphenotyping of Mexican Patients With COVID-19 at Preadmission To Anticipate Severity Stratification: Age-Sex Unbiased Meta-Clustering Technique

Authors of this article:

Lexin Zhou1 Author Orcid Image ;   Nekane Romero-García1 Author Orcid Image ;   Juan Martínez-Miranda2 Author Orcid Image ;   J Alberto Conejero3 Author Orcid Image ;   Juan M García-Gómez1 Author Orcid Image ;   Carlos Sáez1 Author Orcid Image
Article Authors Cited by (4) Tweetations (12) Metrics

Lexin Zhou   1 , BSc ;   Nekane Romero-García   1 , MD ;   Juan Martínez-Miranda   2 , PhD ;   J Alberto Conejero   3 , PhD ;   Juan M García-Gómez   1 , PhD ;   Carlos Sáez   1 , PhD

1 Biomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, Valencia, Spain

2 Centro de Investigación Científica y de Educación Superior de Ensenada, Ensenada, Mexico

3 Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València, Valencia, Spain

Corresponding Author:

  • Carlos Sáez, PhD
  • Biomedical Data Science Lab
  • Instituto Universitario de Tecnologías de la Información y Comunicaciones
  • Universitat Politècnica de València
  • Camino de Vera s/n
  • Valencia, 46022
  • Spain
  • Phone: 34 963877000 ext 75278
  • Email: carsaesi@upv.es