LASSIE : modeling treatment processes using information extraction

Modeling clinical guidelines and protocols in a computer-interpretable format is a challenging, but burdensome and time-consuming task. Existing methods and tools to support this task demand detailed medical knowledge, knowledge about the formal representations, and a manual modeling. Furthermore, formalized guideline documents mostly fall far short in terms of readability and understandability for the human domain modeler. In this thesis we propose a methodology to support the human modeler by both automating parts of the modeling process and making the modeling process traceable and comprehensible.<br />Our methodology called LASSIE (modeLing treAtment proceSSes using Information Extraction), represents a novel step-wise procedure that uses Information Extraction to semi-automatically model treatment processes. We have developed several heuristics without the need to apply Natural Language Understanding. Finally, we integrated our heuristics in a form of a framework and applied them to several guidelines from the medical subject of otolaryngology. The framework has been applied to formalize the guidelines in the formal Asbru plan representation. Findings of our evaluation indicate that using semi-automatic, step-wise Information Extraction methods are a valuable instrument to formalize clinical guidelines and protocols.