Published on in Vol 23, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25988, first published .
Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study

Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study

Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study

Julián Benito-León   1 * , MD, PhD ;   Mª Dolores del Castillo   2 * , PhD ;   Alberto Estirado   3 , BSc ;   Ritwik Ghosh   4 , MD ;   Souvik Dubey   5 , MD, DM ;   J Ignacio Serrano   2 * , PhD

1 Department of Neurology, University Hospital “12 de Octubre”, Madrid, Spain

2 Neural and Cognitive Engineering Group, Center for Automation and Robotics, CSIC-UPM, Arganda del Rey, Spain

3 HM Hospitales, Madrid, Spain

4 Department of General Medicine, Burdwan Medical College and Hospital, Burdwan, India

5 Department of Neuromedicine, Bangur Institute of Neurosciences, Kolkata, India

*these authors contributed equally

Corresponding Author:

  • Julián Benito-León, MD, PhD
  • Department of Neurology
  • University Hospital “12 de Octubre”
  • Avenida de Córdoba s/n
  • Madrid, 28041
  • Spain
  • Phone: 34 639154069
  • Email: jbenitol67@gmail.com