Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system.Patient complexity,illness severity,and the urgency in initiating proper...Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system.Patient complexity,illness severity,and the urgency in initiating proper treatment all contribute to decision-making errors.Clinician-related factors such as fatigue,cognitive overload,and inexperience further interfere with effective decision-making.Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error.This evidence-based review discusses ten common misconceptions regarding critical care decision-making.By understanding how practitioners make clinical decisions and examining how errors occur,strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.展开更多
Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influenc...Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic rea soning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presellted.展开更多
Reiter presented the first formal framework for model-based diagnosis using logic. However, Reiter’s theory is unimplemented because it suffers from some shortcomings. An extension to Reiter’s diagnostic theory is e...Reiter presented the first formal framework for model-based diagnosis using logic. However, Reiter’s theory is unimplemented because it suffers from some shortcomings. An extension to Reiter’s diagnostic theory is established to overcome the shortcomings. Novel features of such extension include: (i) The fault modes of components are introduced to the behavior description, so that the outputs of both normal and abnormal components can be predicted (ii) Domain-dependent heuristics are used to contract and sort the hypothesis space and assist in making measurements, so that the diagnosis efficiency is improved, (iii) An integrated diagnostic system is proposed based on our theory, and efficient algorithms for computing all diagnoses are developed.展开更多
文摘Diagnostic errors are prevalent in critical care practice and are associated with patient harm and costs for providers and the healthcare system.Patient complexity,illness severity,and the urgency in initiating proper treatment all contribute to decision-making errors.Clinician-related factors such as fatigue,cognitive overload,and inexperience further interfere with effective decision-making.Cognitive science has provided insight into the clinical decision-making process that can be used to reduce error.This evidence-based review discusses ten common misconceptions regarding critical care decision-making.By understanding how practitioners make clinical decisions and examining how errors occur,strategies may be developed and implemented to decrease errors in Decision-making and improve patient outcomes.
文摘Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic rea soning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presellted.
基金Project supported by the National Natural Science Foundation of China and Sichuan Youth Science and Technology Foundation
文摘Reiter presented the first formal framework for model-based diagnosis using logic. However, Reiter’s theory is unimplemented because it suffers from some shortcomings. An extension to Reiter’s diagnostic theory is established to overcome the shortcomings. Novel features of such extension include: (i) The fault modes of components are introduced to the behavior description, so that the outputs of both normal and abnormal components can be predicted (ii) Domain-dependent heuristics are used to contract and sort the hypothesis space and assist in making measurements, so that the diagnosis efficiency is improved, (iii) An integrated diagnostic system is proposed based on our theory, and efficient algorithms for computing all diagnoses are developed.
