Using model checking for critiquing based on clinical guidelines. Groot, P., Hommersom, A., Lucas, P. J F, Merk, R., ten Teije, A., van Harmelen, F., & Serban, R. Artificial intelligence in medicine, 46(1):19–36, may, 2009.
Paper doi abstract bibtex OBJECTIVE: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. METHODS AND MATERIAL: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. RESULTS: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.
@article{Groot2009,
abstract = {OBJECTIVE: Medical critiquing systems compare clinical actions performed by a physician with a predefined set of actions. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of 'ideal' actions as described by a clinical guideline. In case differences exist, the critiquing system provides insight into the extent to which they are compatible. METHODS AND MATERIAL: We propose a computational method for such critiquing, where the ideal actions are given by a formal model of a clinical guideline, and where the actual actions are derived from real world patient data. We employ model checking to investigate whether a part of the actual treatment is consistent with the guideline. RESULTS: We show how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. Furthermore, a method is introduced for off-line computing relevant information which can be exploited during critiquing. The method has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.},
author = {Groot, Perry and Hommersom, Arjen and Lucas, Peter J F and Merk, Robbert-Jan and ten Teije, Annette and van Harmelen, Frank and Serban, Radu},
doi = {10.1016/j.artmed.2008.07.007},
file = {:Users/annette/Library/Application Support/Mendeley Desktop/Downloaded/Groot et al. - 2009 - Using model checking for critiquing based on clinical guidelines.pdf:pdf},
issn = {1873-2860},
journal = {Artificial intelligence in medicine},
keywords = {Artificial Intelligence,Breast,Breast Neoplasms,Breast Neoplasms: diagnosis,Breast Neoplasms: therapy,Breast: diagnosis,Breast: therapy,Carcinoma,Clinical,Computer Simulation,Computerized,Decision Support Systems,Ductal,Female,Guideline Adherence,Humans,Logic,Medical Records Systems,Models,Patient Selection,Practice Guidelines as Topic,Systems Integration,Theoretical,Time Factors},
month = {may},
number = {1},
pages = {19--36},
pmid = {18824335},
title = {{Using model checking for critiquing based on clinical guidelines.}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/18824335 http://www.cs.vu.nl/{~}annette/papers-pdf/2009AIMSI.pdf},
volume = {46},
year = {2009}
}
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