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

Decision Support for Health Professionals (1191) Clinical Informatics (1028) Clinical Information and Decision Making (1411) Digital Health, Telehealth and e-Innovation in Clinical Settings (402)

Published on in Vol 2, No 2 (2014): Jul-Dec

Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

Clinical Decision Support System to Enhance Quality Control of Spirometry Using Information and Communication Technologies

Authors of this article:

Felip Burgos1 Author Orcid Image ;   Umberto Melia2 Author Orcid Image ;   Montserrat Vallverdú2 Author Orcid Image ;   Filip Velickovski3, 4 Author Orcid Image ;   Magí Lluch-Ariet3, 5 Author Orcid Image ;   Pere Caminal2 Author Orcid Image ;   Josep Roca1 Author Orcid Image
Article Authors Cited by (13) Tweetations Metrics

Journals

  1. Qvarfordt M, Anderson M, Svartengren M. Quality and learning aspects of the first 9000 spirometries of the LifeGene study. npj Primary Care Respiratory Medicine 2018;28(1) View
  2. Hernández C, Aibar J, Seijas N, Puig I, Alonso A, Garcia-Aymerich J, Roca J. Implementation of Home Hospitalization and Early Discharge as an Integrated Care Service: A Ten Years Pragmatic Assessment. International Journal of Integrated Care 2018;18(0):12 View
  3. Tamire M, Addissie A, Kumie A, Husmark E, Skovbjerg S, Andersson R, Lärstad M. Respiratory Symptoms and Lung Function among Ethiopian Women in Relation to Household Fuel Use. International Journal of Environmental Research and Public Health 2019;17(1):41 View
  4. Martínez Llorens J, Burgos F, Galdiz J. Lung Function is Not Outdated. Archivos de Bronconeumología (English Edition) 2020;56(6):345 View
  5. Velickovski F, Ceccaroni L, Marti R, Burgos F, Gistau C, Alsina-Restoy X, Roca J. Automated Spirometry Quality Assurance: Supervised Learning From Multiple Experts. IEEE Journal of Biomedical and Health Informatics 2018;22(1):276 View
  6. Poly T, Islam M, Yang H, Li Y. Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review. JMIR Medical Informatics 2020;8(7):e15653 View
  7. Vargas C, Burgos F, Cano I, Blanco I, Caminal P, Escarrabill J, Gallego C, Llauger M, Miralles F, Solans O, Vallverdú M, Velickovski F, Roca J. Protocol for regional implementation of collaborative lung function testing. npj Primary Care Respiratory Medicine 2016;26(1) View
  8. . El modelo de atención a crónicos en la EPOC. Archivos de Bronconeumología 2017;53:42 View
  9. Martínez Llorens J, Burgos F, Galdiz J. La función pulmonar no está pasada de moda. Archivos de Bronconeumología 2020;56(6):345 View
  10. Wang Y, Li Y, Chen W, Zhang C, Liang L, Huang R, Liang J, Tu D, Gao Y, Zheng J, Zhong N. Deep learning for spirometry quality assurance with spirometric indices and curves. Respiratory Research 2022;23(1) View
  11. Silveira K, Matos N, Castro T, Souza A, Bezerra O, Bezerra F. The effects of different body positions on pulmonary function in healthy adults. Fisioterapia em Movimento 2022;35 View
  12. Martins C, Barros H, Moreira A. Transfer learning in spirometry: CNN models for automated flow-volume curve quality control in paediatric populations. Computers in Biology and Medicine 2025;184:109341 View

Books/Policy Documents

  1. Roca J, Cano I, Gomez-Cabrero D, Tegnér J. Systems Medicine. View