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We present a new approach to the design of a decision support system (DSS) in anesthesia which converts the available data to relevant information. Instead of a patient-driven design (patient modelling), we use a decision-driven design (anesthetist modelling). This approach results in a system...
This paper describes an informal but systematic method for how to test and verify a knowledge-based system in a large and open-ended medical target domain. The system used is Guardian, an intelligent system for monitoring and diagnosis of post-cardiac surgery patients in an intensive-care unit....
Automating the control of therapy administered to a patient requires systems which integrate the knowledge of experienced physicians. This paper describes NéoGanesh, a knowledge-based system which controls, in closed-loop, the mechanical assistance provided to patients hospitalized in intensive...
The goal of this study was to examine the ability of Neural Networks to recognise the levels of anaesthetic state of a patient. Data obtained under different levels of anaesthesia have been modelled for the purpose. It is shown that inferential parameters can be used to recognise the levels of...
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