@inproceedings{ae8848136e5b4f74a04e3efdedee9bde,
title = "Reasoning with effects of clinical guideline actions using OWL: AL amyloidosis as a case study",
abstract = "We developed an ontology that allows representation and reasoning with effects of clinical actions. The ontology can support three important use-cases: (1) summarization and explanation of observed clinical states, (2) enhancing patient safety using safety rules, and (3) assessing guideline compliance. In this paper we focus on explanation of observed clinical states based on abductive reasoning that utilizes a causal network. We demonstrate our approach using examples taken from a guideline for management of amyloidosis.",
keywords = "OWL, causal models, computer-interpretable guidelines, ontology",
author = "Mor Peleg and Tu, {Samson W.} and Giorgio Leonardi and Silvana Quaglini and Paola Russo and Giovanni Palladini and Giampaolo Merlini",
year = "2012",
doi = "10.1007/978-3-642-27697-2_5",
language = "English",
isbn = "9783642276965",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "65--79",
booktitle = "Knowledge Representation for Health-Care - AIME 2011 Workshop KR4HC 2011, Revised Selected Papers",
note = "3rd International Workshop on Knowledge Representation for Health Care, KR4HC 2011, Held in Conjunction with the 13th Conference on Artificial Intelligence in Medicine, AIME 2011 ; Conference date: 06-07-2011 Through 06-07-2011",
}