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

Letters (85) JMIR Theme Issue: COVID-19 Special Issue (2554) Artificial Intelligence (2129) Clinical Information and Decision Making (1915) Big Data (307) Decision Support for Health Professionals (1539) Electronic Health Records (1319) Natural Language Processing (917) Theme Issue: Medical Informatics and COVID-19 (124) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1542) Intensive Care Unit (ICU) (160) Validity, Reliability, and Bias (110)

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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29405, first published .
Authors’ Reply to: Minimizing Selection and Classification Biases Comment on “Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing”

Authors’ Reply to: Minimizing Selection and Classification Biases Comment on “Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing”

Authors’ Reply to: Minimizing Selection and Classification Biases Comment on “Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing”

Authors of this article:

Jose Luis Izquierdo1 Author Orcid Image ;   Joan B Soriano2 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Jose Luis Izquierdo   1 , MD ;   Joan B Soriano   2 , MD

1 Universidad de Alcalá, Madrid, Spain

2 Hospital Universitario de La Princesa, Madrid, Spain

Corresponding Author:

  • Joan B Soriano, MD
  • Hospital Universitario de La Princesa
  • Diego de Leon 62
  • Servicio de Neumología
  • Madrid 28006
  • Spain
  • Phone: 34 00000000
  • Email: jbsoriano2@gmail.com