A philosophical basis for knowledge acquisition
Knowledge Acquisition
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining data from intensive care patients
Advanced Engineering Informatics
A Human-Machine Cooperative Approach for Time Series Data Interpretation
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Temporal Information Systems in Medicine
Temporal Information Systems in Medicine
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Myocardial damage is known to occur relatively frequently, and although it is not often fatal it results in the patient staying in the ICU for significantly longer. Thus it is important for clinicians to detect these events. Confirmation of myocardial damage is by a biomarker (troponin), but these tests are only done at fixed time-points. Consequently it is desirable for doctors, and support systems, to detect myocardial damage from the standard parameters collected for ICU patients. We have undertaken a study with several ICU consultants to determine the conditions which generally precede a myocardial-damaging event. In fact, these knowledge acquisition sessions produced a complex model which we have realized as 2 interacting modules. Subsequently, we compared this model's predictions against the original datasets; the model when run against the test dataset resulted in a relatively high True Positive (TP) rate (75.8%). The implications of these analyses are discussed, as are a number of planned follow-up studies