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

JMIR Theme Issue: COVID-19 Special Issue (2461) Clinical Information and Decision Making (1436) Machine Learning (1504) Outbreak and Pandemic Preparedness and Management (1743) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Decision Support for Health Professionals (1211) Artificial Intelligence (1427) Infectious Diseases (non-STD/STI) (1592) Theme Issue: Medical Informatics and COVID-19 (107) Data Science (278)

Published on in Vol 23, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26075, first published .
Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study

Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study

Predictability of COVID-19 Hospitalizations, Intensive Care Unit Admissions, and Respiratory Assistance in Portugal: Longitudinal Cohort Study

Authors of this article:

André Patrício1 Author Orcid Image ;   Rafael S Costa2, 3 Author Orcid Image ;   Rui Henriques1, 4 Author Orcid Image
Article Authors Cited by (11) Tweetations (1) Metrics

André Patrício   1 , BSc ;   Rafael S Costa   2, 3 * , PhD ;   Rui Henriques   1, 4 * , PhD

1 Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

2 LAQV-REQUIMTE, NOVA School of Science and Technology, Universidade NOVA de Lisboa, Caparica, Portugal

3 IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal

4 Instituto de Engenharia de Sistemas e Computadores–Investigação e Desenvolvimento, Lisboa, Portugal

*these authors contributed equally

Corresponding Author:

  • Rafael S Costa, PhD
  • LAQV-REQUIMTE
  • NOVA School of Science and Technology
  • Universidade NOVA de Lisboa
  • Campus Caparica, 2829-516
  • Caparica, 2829-516
  • Portugal
  • Phone: 351 21 294 8351
  • Email: rs.costa@fct.unl.pt