Supporting Computer-interpretable Guidelines´ Modeling by Automatically Classifying Clinical Actions

By Anne-Lyse Minard and Katharina Kaiser

Abstract

Modeling computer-interpretable clinical practice guidelines is a complex and tedious task that has been of interest for several attempts to automate parts of this process. When modeling guidelines one of the tasks is to specify common actions in everyday´s practical medicine (e.g., drug prescription, observation) in order to link them with clinical information systems (e.g., an order-entry system). In this paper we compare a rule-based and a machine-learning method to classify activities according to the Clinical Actions Palette used in the Hybrid-Asbru ontology. We use syntactic and semantic features, such as the Semantic Types of the UMLS to classify the activities. Furthermore, we extend our methods by using 2-step classification and combining machine learning and rule-based approaches. Results show that machine learning performs better than the rule-based method on the classification task. They also show that the 2-step classification method improves the categorization of activities.

Reference

A. Minard, K. Kaiser: "Supporting Computer-interpretable Guidelines´ Modeling by Automatically Classifying Clinical Actions"; in: "Process Support and Knowledge Representation in Health Care", D. Riano, R. Lenz, S. Miksch, M. Peleg, M. Reichert, A. ten Teije (ed.); Springer Verlag, LNAI 8268, 2013, ISBN: 978-3-319-03915-2, 39 - 52.

BibTeX

@incollection{TUW-223972, author = {Minard, Anne-Lyse and Kaiser, Katharina}, title = {Supporting Computer-interpretable Guidelines' Modeling by Automatically Classifying Clinical Actions}, booktitle = {Process Support and Knowledge Representation in Health Care}, year = {2013}, editor = {Riano, David and Lenz, Richard and Miksch, Silvia and Peleg, Mor and Reichert, Manfred and ten Teije, Annette}, pages = {39--52}, publisher = {Springer Verlag, LNAI 8268}, url = {http://publik.tuwien.ac.at/files/PubDat_223972.pdf}, isbn = {978-3-319-03915-2}, doi = {10.1007/978-3-319-03916-9{\_}4}, keywords = {Clinical Practice Guidelines, Hybrid-Asbru, Common Clinical Actions, Natural Language Processing, Classification} } Click into the text area and press Ctrl+A/Ctrl+C or ⌘+A/⌘+C to copy the BibTeX into your clipboard… or download the BibTeX.