J Med Syst
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Faced with the opportunity to significantly deviate from classic operations, a new emergency department (ED) and novel strategy for patient care delivery were simultaneously initiated with the aid of model-based simulation. To answer the design and implementation questions, a traditional strategy for construction of discrete-eventmodel simulation was employed to define ED operations for a newly constructed facility in terms of workflow, variables, resources, structure, process logic and associated assumptions. ⋯ Prior to opening, it shed light on the range of context variables where benefits might be anticipated, and it facilitated staff understanding and judgements of performance. Two years after opening, the operations data is compared to the simulation with encouraging results that shed light on where to continue pursuit of improvement.
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Identifying epileptogenic zones prior to surgery is an essential and crucial step in treating patients having pharmacoresistant focal epilepsy. Electroencephalogram (EEG) is a significant measurement benchmark to assess patients suffering from epilepsy. This paper investigates the application of multi-features derived from different domains to recognize the focal and non focal epileptic seizures obtained from pharmacoresistant focal epilepsy patients from Bern Barcelona database. ⋯ Further, it was observed that the classification accuracy improved from 80.2% with outliers to 92.15% without outliers. The classifier performance metrics ensures the suitability of the proposed multi-features with optimized SVM classifier. It can be concluded that the proposed approach can be applied for recognition of focal EEG signals to localize epileptogenic zones.
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The objective of this study was to characterize workload during all hours of the day in the non-operating room anesthesia (NORA) environment and identify what type of patients and procedures were more likely to occur during after-hours. By investigating data from the National Anesthesia Clinical Outcomes Registry, we characterized the total number of ongoing NORA cases per hour of the day (0 - 23 h). Results were presented as the mean hour and standard error (SE). ⋯ Pairwise differences between means for each NORA specialty were all statistically significant (p < 0.0001). During after-hour shifts (4.3% of cases), patients with higher American Society of Anesthesiologists physical status classification scores had increased odds for undergoing a NORA procedure, while procedures that were more physiologically complex had decreased odds. With the increasing demand for NORA services, it is prudent that we fully understand the challenges of providing safe and efficient anesthetic services particularly in locations where fewer resources are available.