OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).
PURPOSE: To evaluate random forests (RFs) as a supervised machine learning algorithm to classify amyloid brain PET as positive or negative for amyloid deposition and identify key regions of interest for stratification.
OBJECTIVES: Visual assessment of the electroencephalogram by experienced clinical neurophysiologists allows reliable outcome prediction of approximately half of all comatose patients after cardiac arrest. Deep neural networks hold promise to achieve ...
INTRODUCTION: Reliable preoperative identification of patients at high risk for early postoperative complications occurring within 24 h (EPC) of intracranial tumor surgery can improve patient safety and postoperative management. Statistical analysis ...
OBJECTIVE: Flares in rheumatoid arthritis (RA) and axial spondyloarthritis (SpA) may influence physical activity. The aim of this study was to assess longitudinally the association between patient-reported flares and activity-tracker-provided steps p...
Studies in health technology and informatics
Sep 3, 2019
The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. In order to enable consortium-wide retrospective research and prospective patient recruitment, we perform data integration into a centra...
Studies in health technology and informatics
Aug 21, 2019
Frequent utilization of the Intensive Care Unit (ICU) is associated with higher costs and decreased availability for patients who urgently need it. Common risk assessment tool, like the ASA score, lack objectivity and do account only for some influen...
BACKGROUND: The use of social media to discuss topics related to and within plastic surgery has become widespread in recent years; however, it remains unclear how to use this abundance of largely untapped data to propagate educational research in the...
IMPORTANCE: Computed tomographic (CT) scanning is the standard for the rapid diagnosis of intracranial injury, but it is costly and exposes patients to ionizing radiation. The Pediatric Emergency Care Applied Research Network (PECARN) rules for ident...
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