An Extension of Chronicles Temporal Model with Taxonomies: Application to Epidemiological Studies

Johanne Bakalara, Johanne Bakalara, Thomas Guyet, Thomas Guyet, Olivier Dameron, André Happe, Emmanuel Oger

2021

Abstract

Medico-administrative databases contain information about patients’ medical events, i.e. their care trajectories. Semantic Web technologies are used by epidemiologists to query these databases in order to identify patients whose care trajectories conform to some criteria. In this article we are interested in care trajectories involving temporal constraints. In such cases, Semantic Web tools lack computational efficiency while temporal pattern matching algorithms are efficient but lack of expressiveness. We propose to use a temporal pattern called chronicles to represent temporal constraints on care trajectories. We also propose an hybrid approach, combining the expressiveness of SPARQL and the efficiency of chronicle recognition to query care trajectories. We evaluate our approach on synthetic data and real large data. The results show that the hybrid approach is more efficient than pure SPARQL, and validate the interest of our tool to detect patients having venous thromboembolism disease in the French medico-administrative database.

Paper Citation

in Harvard Style

Bakalara J., Guyet T., Dameron O., Happe A. and Oger E. (2021). An Extension of Chronicles Temporal Model with Taxonomies: Application to Epidemiological Studies. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF; ISBN 978-989-758-490-9, SciTePress, pages 133-142. DOI: 10.5220/0010236601330142

in Bibtex Style

@conference{healthinf21,
author={Johanne Bakalara and Thomas Guyet and Olivier Dameron and André Happe and Emmanuel Oger},
title={An Extension of Chronicles Temporal Model with Taxonomies: Application to Epidemiological Studies},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF},
year={2021},
pages={133-142},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010236601330142},
isbn={978-989-758-490-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF
TI - An Extension of Chronicles Temporal Model with Taxonomies: Application to Epidemiological Studies
SN - 978-989-758-490-9
AU - Bakalara J.
AU - Guyet T.
AU - Dameron O.
AU - Happe A.
AU - Oger E.
PY - 2021
SP - 133
EP - 142
DO - 10.5220/0010236601330142
PB - SciTePress