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Communication Dans Un Congrès Année : 2020

An extension of chronicles temporal model with taxonomies

Résumé

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.
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Dates et versions

hal-03176657 , version 1 (22-03-2021)

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  • HAL Id : hal-03176657 , version 1

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Johanne Bakalara, Thomas Guyet, Olivier Dameron, André Happe, Emmanuel Oger. An extension of chronicles temporal model with taxonomies: Application to epidemiological studies. BDA 2020 - 36ème Conférence sur la Gestion des Données - Principes, Technologies et Applications, Oct 2020, Virtual, France. pp.1-10. ⟨hal-03176657⟩
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