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 , ES

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

3 HM Hospitales , Madrid , ES

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

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

*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
  • ES
  • Phone: 34 639154069
  • Email: jbenitol67@gmail.com