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These treatment conflicts are subtle and difficult to detect using automated means. Traditional approaches to clinical decision support would require significant clinical knowledge. In this paper, the authors present an alternative approach that relies on encoding treatment protocols via process models (in BPMN) and annotating these models with semantic effect descriptions, which automatically detects conflicts. This paper describes an implemented tool (ProcessSEER) used for semantic effect annotation of a set of 12 cancer trial protocols and depicts the machinery required to detect treatment conflicts. The authors also argue whether the semantic effect annotations of treatment protocols can be leveraged for other tasks.<\/p>","DOI":"10.4018\/jehmc.2010040103","type":"journal-article","created":{"date-parts":[[2010,6,30]],"date-time":"2010-06-30T20:08:25Z","timestamp":1277928505000},"page":"24-35","source":"Crossref","is-referenced-by-count":1,"title":["A Framework for Detecting Interactions Between Co-Incident Clinical Processes"],"prefix":"10.4018","volume":"1","author":[{"given":"Kerry","family":"Hinge","sequence":"first","affiliation":[{"name":"University of Wollongong, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aditya","family":"Ghose","sequence":"additional","affiliation":[{"name":"University of Wollongong, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Miller","sequence":"additional","affiliation":[{"name":"University of Wollongong, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jehmc.2010040103-0","doi-asserted-by":"crossref","unstructured":"Anzb\u00f6ck, R., & Dustdar, S. 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