@inproceedings{
 title = {SWISH for prototyping Clinical Guideline Interactions Theory},
 type = {inproceedings},
 year = {2016},
 keywords = {Clinical guideline interactions,Multimorbidity,Prolog,RDF,SWISH},
 volume = {1795},
 series = {CEUR Workshop Proceedings},
 id = {d3c024c7-ee4a-3617-93cd-1388a669d18a},
 created = {2017-06-06T19:11:32.242Z},
 file_attached = {false},
 profile_id = {aebd07e2-f364-3186-a6b6-baa8ed624f46},
 last_modified = {2017-06-06T19:11:32.242Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {ZamborliniSWAT4LS2016},
 source_type = {proceedings},
 private_publication = {false},
 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.},
 bibtype = {inproceedings},
 author = {Zamborlini, Veruska and Wielemaker, Jan and da Silveira, Marcos and Pruski, Cedric and ten Teije, Annette and van Harmelen, Frank},
 booktitle = {Proceedings of the Workshop on Semantic Web Applications and Tools for Life Sciences, Amsterdam, Netherlands}
}

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