Explainable Decision Support Using Task Network Models in Notation3: Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks

William Van Woensel, Samina Abidi, Karthik Tennankore, George Worthen, Syed Sibte Raza Abidi

Résultat de recherche: Conference contribution

6 Citations (Scopus)

Résumé

Knowledge-driven Clinical Decision Support (CDS) involves the computerization of paper-based clinical guidelines to issue evidence-based recommendations at points-of-care. The computerization of such guidelines in terms of a Task Network Model (TNM) conveniently models them as intuitive workflow models, which can be executed against patient health profiles. We present the GLEAN model that encodes an extensible Finite State Machine (FSM) executional semantics for modular TNM. Extensibility is provided in terms of a high-level formalism for defining execution semantics of custom TNM constructs. GLEAN is implemented using the Notation3 Semantic Web language, which provides powerful features for decisional criteria and queries, and offers integration with the HL7 FHIR standard. We explain CIG workflows as visual, intuitive workflow diagrams that are guided by a concrete patient profile at runtime. As a use case, we computerized guidelines on lipid management for Chronic Kidney Disease (CKD), a challenging problem for many Primary Care Providers (PCPs). To educate PCP on lipid management for CKD, we leverage GLEAN’s easy modularization of CIG and CIG explanations as visual runtime workflows.

Langue d'origineEnglish
Titre de la publication principaleArtificial Intelligence in Medicine - 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, Proceedings
ÉditeursMartin Michalowski, Syed Sibte Raza Abidi, Samina Abidi
Maison d'éditionSpringer Science and Business Media Deutschland GmbH
Pages3-13
Nombre de pages11
ISBN (imprimé)9783031093418
DOI
Statut de publicationPublished - 2022
Événement20th International Conference on Artificial Intelligence in Medicine, AIME 2022 - Halifax, Canada
Durée: juin 14 2022juin 17 2022

Séries de publication

PrénomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13263 LNAI
ISSN (imprimé)0302-9743
ISSN (électronique)1611-3349

Conference

Conference20th International Conference on Artificial Intelligence in Medicine, AIME 2022
Pays/TerritoireCanada
VilleHalifax
Période6/14/226/17/22

Note bibliographique

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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