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Oliveira, B., Mira, M., Monteiro, S., Elvas, L. B., Rosário, L. & Ferreira, J. (2023). Implementing a data integration infrastructure for healthcare data: A case Study. In Ajith Abraham, Anu Bajaj, Niketa Gandhi, Ana Maria Madureira, Cengiz Kahraman (Ed.), Innovations in bio-inspired computing and applications: Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022). (pp. 744-753).: Springer.

B. Oliveira et al.,  "Implementing a data integration infrastructure for healthcare data: A case Study", in Innovations in bio-inspired computing and applications: Proc. of the 13th Int. Conf. on Innovations in Bio-Inspired Computing and Applications (IBICA 2022), Ajith Abraham, Anu Bajaj, Niketa Gandhi, Ana Maria Madureira, Cengiz Kahraman, Ed., Springer, 2023, pp. 744-753

@inproceedings{oliveira2023_1734635793773,
	author = "Oliveira, B. and Mira, M. and Monteiro, S. and Elvas, L. B. and Rosário, L. and Ferreira, J.",
	title = "Implementing a data integration infrastructure for healthcare data: A case Study",
	booktitle = "Innovations in bio-inspired computing and applications: Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022)",
	year = "2023",
	editor = "Ajith Abraham, Anu Bajaj, Niketa Gandhi, Ana Maria Madureira, Cengiz Kahraman",
	volume = "",
	number = "",
	series = "",
	doi = "10.1007/978-3-031-27499-2_69",
	pages = "744-753",
	publisher = "Springer",
	address = "",
	organization = "",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-27499-2_69"
}

TY  - CPAPER
TI  - Implementing a data integration infrastructure for healthcare data: A case Study
T2  - Innovations in bio-inspired computing and applications: Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022)
AU  - Oliveira, B.
AU  - Mira, M.
AU  - Monteiro, S.
AU  - Elvas, L. B.
AU  - Rosário, L.
AU  - Ferreira, J.
PY  - 2023
SP  - 744-753
DO  - 10.1007/978-3-031-27499-2_69
UR  - https://link.springer.com/chapter/10.1007/978-3-031-27499-2_69
AB  - Conducting epidemiologic research usually requires a large amount of data to establish the natural history of a disease and achieve meaningful study design, and interpretations of findings. This is, however, a huge task because the healthcare domain is composed of a complex corpus and concepts that result in difficult ways to use and store data. Additionally, data accessibility should be considered because sensitive data from patients should be carefully protected and shared with responsibility. With the COVID-19 pandemic, the need for sharing data and having an integrated view of the data was reaffirmed to identify the best approaches and signals to improve not only treatments and diagnoses but also social answers to the epidemiological scenario. This paper addresses a data integration scenario for dealing with COVID-19 and cardiovascular diseases, covering the main challenges related to integrating data in a common data repository storing data from several hospitals. Conceptual architecture is presented to deal with such approaches and integrate data from a Portuguese hospital into the common repository used to explore data in a standardized way.
ER  -