Medical critiquing systems criticise clinical actions performed by a physician. 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, insight to which extent they are compatible is provided by the critiquing system. We propose a methodology 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. Furthermore, it is shown how critiquing can be cast in terms of temporal logic, and what can be achieved by using model checking. The methodology has been applied to a clinical guideline of breast cancer in conjunction with breast cancer patient data.
|Title of host publication||Artificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings|
|Number of pages||10|
|Publication status||Published - 2007|
|Event||11th Conference on Artificial Intelligence in Medicine, AIME 2007 - Amsterdam, Netherlands|
Duration: 7 Jul 2007 → 11 Jul 2007
|Conference||11th Conference on Artificial Intelligence in Medicine, AIME 2007|
|Period||7/07/07 → 11/07/07|