Publications by authors named "Eric M Christiansen"

Purpose: We determined the incidence of epidural fluid signal on spinal magnetic resonance imaging (MRI) after image-guided lumbar puncture (LP) in adults. We correlated those imaging findings with clinical status.

Methods: We searched our institution's medical records from January 2013 through April 2020 to identify adult patients who underwent image-guided LP and postdural puncture MRI.

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Background: Percutaneous cholecystostomy tube (PTGBD), endoscopic retrograde cholangiopancreatography with transpapillary gallbladder drainage (TP), and endoscopic ultrasound-guided transmural gallbladder drainage (EGBD) using lumen-apposing metal stents (LAMS) have been offered for gallbladder decompression for acute cholecystitis in high-risk surgical patients. Yet, there are limited data comparing these therapies. Our aim was to compare the safety and efficacy of EGBD to TP and PTGBD for gallbladder drainage.

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Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement.

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Research has shown that inverting faces significantly disrupts the processing of configural information, leading to a face inversion effect. We recently used a contextual priming technique to show that the presence or absence of the face inversion effect can be determined via the top-down activation of face versus non-face processing systems [Ge, L., Wang, Z.

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Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. However, their performance on natural language tasks has been largely unexplored until now. Simple Recurrent Networks (SRNs) have a long history in language modeling and show a striking similarity in architecture to ESNs.

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