Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials.

Background: Systematic reviews of Randomized Controlled Trials (RCTs) are an important part of the evidence-based medicine paradigm. However, the creation of such systematic reviews by clinical experts is costly as well as time-consuming, and results can get quickly outdated after publication. Most RCTs are structured based on the Patient, Intervention, Comparison, Outcomes (PICO) framework and there exist many approaches which aim to extract PICO elements automatically.

Exploring the scope of post-intensive care syndrome therapy and care: engagement of non-critical care providers and survivors in a second stakeholders meeting.

Background: Increasing numbers of survivors of critical illness are at risk for physical, cognitive, and/or mental health impairments that may persist for months or years after hospital discharge. The post-intensive care syndrome framework encompassing these multidimensional morbidities was developed at the 2010 Society of Critical Care Medicine conference on improving long-term outcomes after critical illness for survivors and their families.

Objectives: To report on engagement with non-critical care providers and survivors during the 2012 Society of Critical Care Medicine post-intensive care syndrome stakeholder conference.

Long-term persistence of quality improvements for an intensive care unit communication initiative using the VALUE strategy.

Purpose: Communication in the intensive care unit (ICU) is an important component of quality ICU care. In this report, we evaluate the long-term effects of a quality improvement (QI) initiative, based on the VALUE communication strategy, designed to improve communication with family members of critically ill patients.

Materials And Methods: We implemented a multifaceted intervention to improve communication in the ICU and measured processes of care.

Comparison of glomerular filtration rate determined by use of single-slice dynamic computed tomography and scintigraphy in cats.

Objective: To compare estimation of glomerular filtration rate determined via conventional methods (ie, scintigraphy and plasma clearance of technetium Tc 99m pentetate) and dynamic single-slice computed tomography (CT).

Animals: 8 healthy adult cats.

Procedures: Scintigraphy, plasma clearance testing, and dynamic CT were performed on each cat on the same day; order of examinations was randomized.

Improving long-term outcomes after discharge from intensive care unit: report from a stakeholders' conference.

Background: Millions of patients are discharged from intensive care units annually. These intensive care survivors and their families frequently report a wide range of impairments in their health status which may last for months and years after hospital discharge.

Objectives: To report on a 2-day Society of Critical Care Medicine conference aimed at improving the long-term outcomes after critical illness for patients and their families.

Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC.

A number of brain imaging techniques have been developed in order to investigate brain function and to develop diagnostic tools for various brain disorders. Each modality has strengths as well as weaknesses compared to the others. Recent work has explored how multiple modalities can be integrated effectively so that they complement one another while maintaining their individual strengths.

Probabilistic forward model for electroencephalography source analysis.

Source localization by electroencephalography (EEG) requires an accurate model of head geometry and tissue conductivity. The estimation of source time courses from EEG or from EEG in conjunction with magnetoencephalography (MEG) requires a forward model consistent with true activity for the best outcome. Although MRI provides an excellent description of soft tissue anatomy, a high resolution model of the skull (the dominant resistive component of the head) requires CT, which is not justified for routine physiological studies.

Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data.

The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse.

Improving source detection and separation in a spatiotemporal Bayesian inference dipole analysis.

Most existing spatiotemporal multi-dipole approaches for MEG/EEG source localization assume that the dipoles are active for the full time range being analysed. If the actual time range of activity of sources is significantly shorter than the time range being analysed, the detectability, localization and time-course determination of such sources may be adversely affected, especially for weak sources. In order to improve detectability and reconstruction of such sources, it is natural to add active time range information (starting time point and ending time point of source activation) for each candidate source as unknown parameters in the analysis.

Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data.

Recently, we described a Bayesian inference approach to the MEG/EEG inverse problem that used numerical techniques to estimate the full posterior probability distributions of likely solutions upon which all inferences were based [Schmidt, D.M., George, J.