[Zurück]

R. Wenzina, K. Kaiser:
"Identifying Condition-Action Sentences Using a Heuristic-Based Information Extraction Method";
in: "Process Support and Knowledge Representation in Health Care", D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, A. ten Teije (Hrg.); Springer Verlag, LNAI 8268, 2013, ISBN: 978-3-319-03915-2, S. 26 - 38.

Translating clinical practice guidelines into a computer-interpretable format is a challenging and laborious task. In this project we focus on supporting the early steps of the modeling process by automatically identifying conditional activities in guideline documents in order to model them automatically in further consequence. Therefore, we developed a rule-based, heuristic method that combines domain-independent information extraction rules and semantic pattern rules. The classification also uses a weighting coefficient to verify the relevance of the sentence in the context of other information aspects, such as effects, intentions, etc. Our evaluation results show that even with a small set of training data, we achieved a recall of 75 % and a precision of 88 %. This outcome shows that this method supports the modeling task and eases the translation of CPGs into a semi-formal model.

computer-interpretable clinical guidelines, medical guideline formalization, Many-Headed Bridge (MHB), UMLS, Information Extraction (IE)

http://dx.doi.org/10.1007/978-3-319-03916-9_3

http://publik.tuwien.ac.at/files/PubDat_223973.pdf

Projektleitung Katharina Kaiser:
Unterstützung für Entwicklung und Transformation von medizinischen Leitlinien und Protokollen