Abstract
The Intensive Care Unit (ICU) provides treatment to critically ill patient's. When a patient does not respond as expected to such treatment it can be challenging for clinicians, especially junior clinicians, as they may not have the relevant experience to understand the patient's anomalous response. Datasets for 10 patients from Glasgow Royal Infirmary's ICU have been made available to its. We asked several ICU clinicians to review these datasets and to suggest. sequences which include anomalous or unusual reactions to treatment. Further, we then asked two ICU clinicians if they agreed with their colleagues assessments, and if they did to provide possible explanations for these anomalous sequences. Subsequently we have developed a system which is able to replicate the clinicians' explanations based on the knowledge contained in its several ontologies: further the system can suggest additional explanations which will be evaluated by the senior consultant.
Original language | English |
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Pages (from-to) | 250-254 |
Number of pages | 5 |
Journal | Lecture Notes in Computer Science |
Volume | 5651 |
DOIs | |
Publication status | Published - 2009 |
Event | 12th Conference on Artificial Intelligence in Medicine, AIME 2009 - Verona, Italy Duration: 18 Jul 2009 → 22 Jul 2009 |
Keywords
- anomalies
- knowledge Based systems