PROJECT TITLE :
Clinical Decision Support and Closed-Loop Control for Cardiopulmonary Management and Intensive Care Unit Sedation Using Expert Systems
Patients within the intensive care unit (ICU) who require mechanical ventilation because of acute respiratory failure also frequently require the administration of sedative agents. The requirement for sedation arises each from patient anxiety due to the loss of non-public management and therefore the unfamiliar and intrusive setting of the ICU, and additionally due to pain or other variants of noxious stimuli. Whereas physicians select the agent(s) used for sedation and cardiovascular perform, the particular administration of these agents is the responsibility of the nursing workers. If clinical decision support systems and closed-loop control systems may be developed for critical care monitoring and lifesaving interventions moreover because the administration of sedation and cardiopulmonary management, the ICU nurse could be released from the extreme monitoring of sedation, allowing her/him to target alternative crucial tasks. One significantly attractive strategy is to utilize the knowledge and experience of skilled clinicians, capturing explicitly the foundations professional clinicians use to determine on how to titrate drug doses relying on the amount of sedation. During this paper, we tend to extend the deterministic rule-primarily based knowledgeable system for cardiopulmonary management and ICU sedation framework presented in to a stochastic setting by using likelihood theory to quantify uncertainty and hence cope with additional realistic clinical situations.
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