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This paper presents a control strategy for exact reference tracking in the presence of parameter uncertainty for the NeuroMuscular Blockade (NMB) level of patients undergoing general anesthesia. For this control application, a compartmental realization of a minimally parameterized Wiener model was used in [1] in which the parameters were estimated from a bank of collected real data using the Extended...
Real-world databases often contain missing data and existing correction algorithms deliver varying performance. Also, most modeling techniques are not suitable to deal with them automatically. In this study we examine different approaches to predicting septic shock in the presence of missing data. Some preprocessing techniques for managing missing data include disregarding data, or replacing it with...
A recursive system identification algorithm that merges PK/PD information in a minimally parameterized Wiener model for the NMB level is presented. The results show that the coupling between one parameter from the linear block and one from the static nonlinearity is advantageous, when evaluated on a database of 60 real collected NMB cases.
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