Solving the frame problem: a mathematical investigation of the common sense law of inertia
Solving the frame problem: a mathematical investigation of the common sense law of inertia
IEEE Intelligent Systems
Evidence-based careflow management systems: the case of post-stroke rehabilitation
Journal of Biomedical Informatics
The PROGEMM Approach For Managing Clinical Processes
WETICE '03 Proceedings of the Twelfth International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises
Logic in Computer Science: Modelling and Reasoning about Systems
Logic in Computer Science: Modelling and Reasoning about Systems
Semantic Clinical Process Management
CBMS '07 Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems
IEEE Intelligent Systems
Towards an Enterprise Business Process Architecture Standard
SERVICES '08 Proceedings of the 2008 IEEE Congress on Services - Part I
Process SEER: A Tool for Semantic Effect Annotation of Business Process Models
EDOC '09 Proceedings of the 2009 IEEE International Enterprise Distributed Object Computing Conference (edoc 2009)
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The detection of treatment conflicts between multiple treatment protocols that are co-incident is a difficult and open problem that is particularly exacerbated regarding the treatment of multiple medical conditions co-occurring in aged patients. For example, a clinical protocol for prostate cancer treatment requires the administration of androgen-suppressing medication, which may negatively interact with another, co-incident protocol if the same patient were being treated for renal disease via haemodialysis, where androgen-enhancers are frequently administered. 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.