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

Decision Support for Health Professionals (1163) Clinical Information and Decision Making (1374) Continuing Medical Education (CME) for Doctors (123) Intensive Care Unit (ICU) (109)

Published on in Vol 7, No 4 (2019): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15358, first published .
A Bayesian Network Analysis of the Diagnostic Process and its Accuracy to Determine How Clinicians Estimate Cardiac Function in Critically Ill Patients: Prospective Observational Cohort Study

A Bayesian Network Analysis of the Diagnostic Process and its Accuracy to Determine How Clinicians Estimate Cardiac Function in Critically Ill Patients: Prospective Observational Cohort Study

A Bayesian Network Analysis of the Diagnostic Process and its Accuracy to Determine How Clinicians Estimate Cardiac Function in Critically Ill Patients: Prospective Observational Cohort Study

Authors of this article:

Thomas Kaufmann1 Author Orcid Image ;   José Castela Forte1, 2, 3, 4 Author Orcid Image ;   Bart Hiemstra1, 2 Author Orcid Image ;   Marco A Wiering4 Author Orcid Image ;   Marco Grzegorczyk4 Author Orcid Image ;   Anne H Epema1 Author Orcid Image ;   Iwan C C van der Horst2, 5 Author Orcid Image ;   SICS Study Group6
Article Authors Cited by (3) Tweetations (3) Metrics

Thomas Kaufmann   1 * , MD ;   José Castela Forte   1, 2, 3, 4 * , BSc ;   Bart Hiemstra   1, 2 , MD, PhD ;   Marco A Wiering   4 , PhD ;   Marco Grzegorczyk   4 , PhD ;   Anne H Epema   1 , MD, PhD ;   Iwan C C van der Horst   2, 5 , MD, PhD ;   SICS Study Group   6

1 Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands

2 Department of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, Netherlands

3 Department of Clinical Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands

4 Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Groningen, Netherlands

5 Department of Intensive Care, Maastricht University Medical Center+, Maastricht University, Maastricht, Netherlands

6 remove, remove, Netherlands

*these authors contributed equally

Corresponding Author:

  • Thomas Kaufmann, MD
  • Department of Anesthesiology
  • University Medical Center Groningen
  • University of Groningen
  • Hanzeplein 1
  • PO Box 30.001
  • Groningen, 9700 RB
  • Netherlands
  • Phone: 31 503616161
  • Email: t.kaufmann@umcg.nl