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A method for the graphical modeling of relative temporal constraints.
Mate, Sebastian; Bürkle, Thomas; Kapsner, Lorenz A; Toddenroth, Dennis; Kampf, Marvin O; Sedlmayr, Martin; Castellanos, Ixchel; Prokosch, Hans-Ulrich; Kraus, Stefan.
Afiliación
  • Mate S; Medical Centre for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany. Electronic address: sebastian.mate@uk-erlangen.de.
  • Bürkle T; Bern University of Applied Sciences, Biel, Switzerland.
  • Kapsner LA; Medical Centre for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Toddenroth D; Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Kampf MO; Medical Centre for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Sedlmayr M; Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
  • Castellanos I; Department of Anesthesiology, Universitätsklinikum Erlangen, Erlangen, Germany.
  • Prokosch HU; Medical Centre for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany; Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
  • Kraus S; Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
J Biomed Inform ; 100: 103314, 2019 12.
Article en En | MEDLINE | ID: mdl-31629921
ABSTRACT
Searching for patient cohorts in electronic patient data often requires the definition of temporal constraints between the selection criteria. However, beyond a certain degree of temporal complexity, the non-graphical, form-based approaches implemented in current translational research platforms may be limited when modeling such constraints. In our opinion, there is a need for an easily accessible and implementable, fully graphical method for creating temporal queries. We aim to respond to this challenge with a new graphical notation. Based on Allen's time interval algebra, it allows for modeling temporal queries by arranging simple horizontal bars depicting symbolic time intervals. To make our approach applicable to complex temporal patterns, we apply two extensions with duration intervals, we enable the inference about relative temporal distances between patient events, and with time interval modifiers, we support counting and excluding patient events, as well as constraining numeric values. We describe how to generate database queries from this notation. We provide a prototypical implementation, consisting of a temporal query modeling frontend and an experimental backend that connects to an i2b2 system. We evaluate our modeling approach on the MIMIC-III database to demonstrate that it can be used for modeling typical temporal phenotyping queries.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Gráficos por Computador / Simulación por Computador Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Gráficos por Computador / Simulación por Computador Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: J Biomed Inform Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article