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

Digital Health Reviews (1331) Decision Support for Health Professionals (1211) Machine Learning (1505) Artificial Intelligence (1430) Clinical Information and Decision Making (1438)

Published on in Vol 24, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39452, first published .
Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review

Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review

Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review

Authors of this article:

Daniela Ferreira-Santos1, 2 Author Orcid Image ;   Pedro Amorim1, 2, 3 Author Orcid Image ;   Tiago Silva Martins2 Author Orcid Image ;   Matilde Monteiro-Soares1, 2, 4 Author Orcid Image ;   Pedro Pereira Rodrigues1, 2 Author Orcid Image
Article Authors Cited by (19) Tweetations (5) Metrics

Daniela Ferreira-Santos   1, 2 , MSc ;   Pedro Amorim   1, 2, 3 , MSc ;   Tiago Silva Martins   2 , MSc ;   Matilde Monteiro-Soares   1, 2, 4 , PhD ;   Pedro Pereira Rodrigues   1, 2 , PhD

1 Department of Community Medicine, Information and Decision Sciences, Faculty of Medicine, University of Porto, Porto, Portugal

2 Center for Health Technology and Services Research, Porto, Portugal

3 Sleep and Non-Invasive Ventilation Unit, São João University Hospital, Porto, Portugal

4 Portuguese Red Cross Health School Lisbon, Lisbon, Portugal

Corresponding Author:

  • Daniela Ferreira-Santos, MSc
  • Department of Community Medicine, Information and Decision Sciences
  • Faculty of Medicine, University of Porto
  • Rua Dr Plácido da Costa, s/n
  • Porto, 4200-450
  • Portugal
  • Phone: 351 937710766
  • Email: danielasantos@med.up.pt