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Real time expert systems can be helpful to the anesthetist, being in charge of monitoring signals coming from the patient during an operation. The large stream of data can be organized, validated and interpreted by such an intelligent system. A physical model of the patient which is able to simulate the signals that are measured at an actual patient, combined with actual anesthesia equipment, can provide the signals, originating from known faults, from which the knowledge which forms the core of the expert system can be derived. Instead of physical patient models and actual equipment, mathematical models can be used for this task. Mathematical models are more flexible and cheaper than physical models. Our approach, in which we combine knowledge based methods with mathematical simulation models is described in this paper. The medical problem domain will be artificial ventilation of a patient during anesthesia.
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