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

Ontologies, Classifications, and Coding (237) eHealth Infrastructures (333) Standards and Interoperability (71)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17176, first published .
Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability

Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability

Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability

Authors of this article:

Felipe Carvalho Pellison1 Author Orcid Image ;   Rui Pedro Charters Lopes Rijo2, 3, 4, 5 Author Orcid Image ;   Vinicius Costa Lima1 Author Orcid Image ;   Nathalia Yukie Crepaldi6 Author Orcid Image ;   Filipe Andrade Bernardi1 Author Orcid Image ;   Rafael Mello Galliez7 Author Orcid Image ;   Afrânio Kritski7 Author Orcid Image ;   Kumar Abhishek8 Author Orcid Image ;   Domingos Alves5 Author Orcid Image
Article Authors Cited by (16) Tweetations (1) Metrics

Journals

  1. Das S, Rahman M. A middleware architecture to integrate and share health data from heterogeneous and diverse data sources. Iran Journal of Computer Science 2022;5(3):267 View
  2. Fuad A, Herwanto G, Pertiwi A, Wahyuningtias S, Harsini H, Maula A, Putri D, Probandari A, Ahmad R. Design and prototype of TOMO: an app for improving drug resistant TB treatment adherence. F1000Research 2021;10:983 View
  3. Lima V, Bernardi F, Domingues M, Kritski A, Lopes Rijo R, Alves D. A computational infrastructure for semantic data integration towards a patient-centered database for Tuberculosis care. Procedia Computer Science 2022;196:434 View
  4. Silva M, Durovini P, Mota P, Kritski A. Fatores associados à subnotificação de casos de tuberculose multirresistente no Estado do Rio de Janeiro, Brasil: relacionamento probabilístico entre sistemas de informação. Cadernos de Saúde Pública 2021;37(10) View
  5. Min L, Atalag K, Tian Q, Chen Y, Lu X. Verifying the Feasibility of Implementing Semantic Interoperability in Different Countries Based on the OpenEHR Approach: Comparative Study of Acute Coronary Syndrome Registries. JMIR Medical Informatics 2021;9(10):e31288 View
  6. Zhang H, Lyu T, Yin P, Bost S, He X, Guo Y, Prosperi M, Hogan W, Bian J. A scoping review of semantic integration of health data and information. International Journal of Medical Informatics 2022;165:104834 View
  7. Crepaldi N, Lima V, Bernardi F, Alves D. An information system for monitoring tuberculosis cases: implementation research protocol using RE-AIM for a health region in Brazil. Procedia Computer Science 2023;219:1128 View
  8. Yamaguti V, Freitas A, Apunike A, Rijo R, Alves D, Netto A. Clinical Pathways and Hierarchical Clustering for Tuberculosis Treatment Outcome Prediction. Procedia Computer Science 2023;219:1373 View
  9. Perrin Franck C, Babington-Ashaye A, Dietrich D, Bediang G, Veltsos P, Gupta P, Juech C, Kadam R, Collin M, Setian L, Serrano Pons J, Kwankam S, Garrette B, Barbe S, Bagayoko C, Mehl G, Lovis C, Geissbuhler A. iCHECK-DH: Guidelines and Checklist for the Reporting on Digital Health Implementations. Journal of Medical Internet Research 2023;25:e46694 View
  10. Bernardi F, Alves D, Crepaldi N, Yamada D, Lima V, Rijo R. Data Quality in Health Research: Integrative Literature Review. Journal of Medical Internet Research 2023;25:e41446 View
  11. Mozini M, Rothschild R, Mioto A, Bernardi F, Lima V, Soares G, Segamarchi R, Alves D. OUTB: application for decision-support in the outcomes of Tuberculosis. Procedia Computer Science 2024;239:832 View

Books/Policy Documents

  1. de Oliveira Vargas Yamada T, Nascimento Almeida F. Blockchain Applications in the Smart Era. View
  2. Lima V, Crepaldi N, Bernardi F, Segamarchi R, Alves D. Information Management. View