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

Theme Issue 2021: Health Natural Language Processing and Applications (16) Electronic Health Records (747) Natural Language Processing (470) Machine Learning (953) Decision Support for Health Professionals (697) Clinical Information and Decision Making (855) Clinical Informatics (514) Stroke (109) Secondary Use of Clinical Data for Research and Surveillance (248) Ontologies, Classifications, and Coding (158)

Published on in Vol 9 , No 11 (2021) :November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29120, first published .
Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers

Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers

Stroke Outcome Measurements From Electronic Medical Records: Cross-sectional Study on the Effectiveness of Neural and Nonneural Classifiers

Authors of this article:

Bruna Stella Zanotto 1, 2 Author Orcid Image ;   Ana Paula Beck da Silva Etges 1, 3 Author Orcid Image ;   Avner dal Bosco 3 Author Orcid Image ;   Eduardo Gabriel Cortes 4 Author Orcid Image ;   Renata Ruschel 1 Author Orcid Image ;   Ana Claudia De Souza 5 Author Orcid Image ;   Claudio M V Andrade 6 Author Orcid Image ;   Felipe Viegas 6 Author Orcid Image ;   Sergio Canuto 6 Author Orcid Image ;   Washington Luiz 6 Author Orcid Image ;   Sheila Ouriques Martins 5 Author Orcid Image ;   Renata Vieira 7 Author Orcid Image ;   Carisi Polanczyk 1, 2 Author Orcid Image ;   Marcos André Gonçalves 6 Author Orcid Image
Article Authors Cited by Tweetations (11) Metrics
Bruna Stella Zanotto 1, 2 * , MSc, PharmD ;   Ana Paula Beck da Silva Etges 1, 3 * , Eng, MSc, PhD ;   Avner dal Bosco 3 * , MSc ;   Eduardo Gabriel Cortes 4 * , MSc ;   Renata Ruschel 1 * , PT ;   Ana Claudia De Souza 5 * , MD, PhD ;   Claudio M V Andrade 6 * , MSc ;   Felipe Viegas 6 * , MSc ;   Sergio Canuto 6 * , MSc, PhD ;   Washington Luiz 6 * , MSc ;   Sheila Ouriques Martins 5 * , MSc, MD, PhD ;   Renata Vieira 7 * , MSc, PhD ;   Carisi Polanczyk 1, 2 * , MSc, MD, PhD ;   Marcos André Gonçalves 6 * , MSc, PhD

1 National Institute of Health Technology Assessment - INCT/IATS (CNPQ 465518/2014-1) , Universidade Federal do Rio Grande do Sul , Porto Alegre , BR

2 Graduate Program in Epidemiology , Universidade Federal do Rio Grande do Sul , Porto Alegre , BR

3 School of Technology , Pontifícia Universidade Católica do Rio Grande do Sul , Porto Alegre , BR

4 Graduate Program of Computer Science , Universidade Federal do Rio Grande do Sul , Porto Alegre , BR

5 Brazilian Stroke Network , Hospital Moinhos de Vento , Porto Alegre , BR

6 Computer Science Department , Universidade Federal de Minas Gerais , Belo Horizonte , BR

7 Centro Interdisciplinar de História, Culturas e Sociedades (CIDEHUS) , Universidade de Évora , Évora , PT

*all authors contributed equally

Corresponding Author:

  • Marcos André Gonçalves, MSc, PhD
  • Computer Science Department
  • Universidade Federal de Minas Gerais
  • Avenue Antônio Carlos, 6627
  • Belo Horizonte
  • BR
  • Phone: 55 3134095860
  • Email: mgoncalv@dcc.ufmg.br