SWISH for prototyping clinical guideline interactions theory

Veruska Carretta Zamborlini, Jan Wielemaker, Marcos Da Silveira, Cedric Pruski, Annette ten Teije, F.A.H. van Harmelen

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

SWISH provides a general purpose collaborative infrastructure for applying Prolog reasoning over an RDF dataset together with features that facilitates prototyping Semantic Web applications. In this paper we report on the use of SWISH for efficiently developing a prototype for detection of clinical guideline interactions. These guidelines are a set of medical recommendations meant for supporting doctors on tackling a single disease. However, often guidelines need to be combined for treating patients that suffer from multiple diseases, and then a number of interactions can occur. The generic interaction rules are implemented in SWI-Prolog and the guideline RDF-data is enriched with clinical Linked Open Data (LOD) (e.g. Drugbank, Sider). We show the implementation of the proposed theory about interaction detection in a case-study on combining three guidelines. The experiment is interactively described using a SWISH notebook and the results are graphical visualised empowered by graphviz.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1795
Publication statusPublished - 2016

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Semantic Web
Experiments

Keywords

  • Clinical guideline interactions
  • Multimorbidity
  • Prolog
  • RDF
  • SWISH

Cite this

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abstract = "SWISH provides a general purpose collaborative infrastructure for applying Prolog reasoning over an RDF dataset together with features that facilitates prototyping Semantic Web applications. In this paper we report on the use of SWISH for efficiently developing a prototype for detection of clinical guideline interactions. These guidelines are a set of medical recommendations meant for supporting doctors on tackling a single disease. However, often guidelines need to be combined for treating patients that suffer from multiple diseases, and then a number of interactions can occur. The generic interaction rules are implemented in SWI-Prolog and the guideline RDF-data is enriched with clinical Linked Open Data (LOD) (e.g. Drugbank, Sider). We show the implementation of the proposed theory about interaction detection in a case-study on combining three guidelines. The experiment is interactively described using a SWISH notebook and the results are graphical visualised empowered by graphviz.",
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SWISH for prototyping clinical guideline interactions theory. / Carretta Zamborlini, Veruska; Wielemaker, Jan; Da Silveira, Marcos; Pruski, Cedric; ten Teije, Annette; van Harmelen, F.A.H.

In: CEUR Workshop Proceedings, Vol. 1795, 2016.

Research output: Contribution to JournalArticleAcademicpeer-review

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T1 - SWISH for prototyping clinical guideline interactions theory

AU - Carretta Zamborlini, Veruska

AU - Wielemaker, Jan

AU - Da Silveira, Marcos

AU - Pruski, Cedric

AU - ten Teije, Annette

AU - van Harmelen, F.A.H.

PY - 2016

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AB - SWISH provides a general purpose collaborative infrastructure for applying Prolog reasoning over an RDF dataset together with features that facilitates prototyping Semantic Web applications. In this paper we report on the use of SWISH for efficiently developing a prototype for detection of clinical guideline interactions. These guidelines are a set of medical recommendations meant for supporting doctors on tackling a single disease. However, often guidelines need to be combined for treating patients that suffer from multiple diseases, and then a number of interactions can occur. The generic interaction rules are implemented in SWI-Prolog and the guideline RDF-data is enriched with clinical Linked Open Data (LOD) (e.g. Drugbank, Sider). We show the implementation of the proposed theory about interaction detection in a case-study on combining three guidelines. The experiment is interactively described using a SWISH notebook and the results are graphical visualised empowered by graphviz.

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