Generation of non-compliant behaviour in virtual medical narratives

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Authors: Lindsay, A., Charles, F., Read, J., Porteous, J., Cavazza, M. and Georg, G.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 9238

Pages: 216-228

eISSN: 1611-3349

ISBN: 9783319219950

ISSN: 0302-9743

DOI: 10.1007/978-3-319-21996-7_22

© Springer International Publishing Switzerland 2015. Patient education documents increasingly take the form of Patient Guidelines, which share many of the properties of clinical guidelines in terms of knowledge content and the description of clinical protocols. They however differ in one specific aspect, which is that some recommendations for patient behaviour may be violated, and that no explicit representation of undesired behaviour is embedded in the guidelines themselves. In this paper, we take as a starting point the planbased representation of clinical guidelines, which has been promoted by several authors, and introduce a method to automatically derive the set of “opposite actions” that constitute violations of recommended patient behaviours. These additional alternative actions are generated automatically as PDDL operators complementing the description of the guideline. As an application, using a patient guideline on bariatric surgery, we also present examples of how these actions can be used to visualise undesirable patient behaviour in a 3D serious game, featuring virtual agents representing the patient and healthcare professionals.

This data was imported from Web of Science (Lite):

Authors: Lindsay, A., Charles, F., Read, J., Porteous, J., Cavazza, M. and Georg, G.

Journal: INTELLIGENT VIRTUAL AGENTS, IVA 2015

Volume: 9238

Pages: 216-228

ISBN: 978-3-319-21995-0

ISSN: 0302-9743

DOI: 10.1007/978-3-319-21996-7_22

The data on this page was last updated at 04:55 on May 22, 2019.