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Authors: Sina Namaki Araghi ; Franck Fontanili ; Elyes Lamine ; Nicolas Salatge and Frederick Benaben

Affiliation: Industrial Engineering Center of IMT Mines Albi , University of Toulouse, Albi 81000, France.

Keyword(s): Model-driven Engineering, Process Mining, Indoor Localization Systems (ILS), Patient Pathways.

Abstract: The application of indoor localization and process mining emerges as an intriguing tool for the researchers to address the structural issues related to the patient pathways inside healthcare organizations. However, there is a major gap in the literature. This is related to the lack of enough attention to the interpretation of location data. Therefore, as a contribution, this article presents the DIAG meta-model and relevant location data interpretation rules. This model-driven approach has been realized in the context of the R-IOSUITE application and it supports the further analyses by the process mining methods.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Araghi, S.; Fontanili, F.; Lamine, E.; Salatge, N. and Benaben, F. (2020). Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - HEALTHINF; ISBN 978-989-758-398-8; ISSN 2184-4305, SciTePress, pages 472-481. DOI: 10.5220/0008971104720481

@conference{healthinf20,
author={Sina Namaki Araghi. and Franck Fontanili. and Elyes Lamine. and Nicolas Salatge. and Frederick Benaben.},
title={Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - HEALTHINF},
year={2020},
pages={472-481},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008971104720481},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - HEALTHINF
TI - Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations
SN - 978-989-758-398-8
IS - 2184-4305
AU - Araghi, S.
AU - Fontanili, F.
AU - Lamine, E.
AU - Salatge, N.
AU - Benaben, F.
PY - 2020
SP - 472
EP - 481
DO - 10.5220/0008971104720481
PB - SciTePress