Forecasting the future of smart hospitals: findings from a real-time delphi study.

Background: In concert with other digital technologies, artificial intelligence (AI) is shaping the vision of smart hospitals. The transformation into smart hospitals, however, is all but trivial due to the lack of financial and human resources, digital skills, and supporting policies. Thus, the extent to which the vision of smart hospitals will eventually become reality is uncertain.

Cosmic dust impacts on the Hubble Space Telescope.

Exposure of the Hubble Space Telescope to space in low Earth orbit resulted in numerous hypervelocity impacts by cosmic dust (micrometeoroids) and anthropogenic particles (orbital debris) on the solar arrays and the radiator shield of the Wide Field and Planetary Camera 2, both subsequently returned to Earth. Solar cells preserve residues from smaller cosmic dust (and orbital debris) but give less reliable information from larger particles. Here, we present images and analyses from electron, ion and X-ray fluorescence microscopes for larger impact features (millimetre- to centimetre-scale) on the radiator shield.

Detection and Quantification of Extraterrestrial Platinum Group Element Alloy Micronuggets from Archean Impactite Deposits by Low-Voltage Scanning Electron Microscopy/Energy-Dispersive X-ray Spectrometry.

Rare, heterogeneously composed platinum group element alloy micronuggets (PGNs) occur in primitive meteorites, micrometeorites, and terrestrial impactite deposits. To gain insight into the nature of these phases, we developed a workflow for the characterization of PGNs using modern scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry at a low accelerating voltage of 6 kV. Automated feature analysis-a combination of morphological image analysis and elemental analysis with stage control-allowed us to detect PGNs down to 200 nm over a relatively large analysis area of 53 mm2 with a conventional silicon drift detector (SDD).

[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].

Background: High expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma patients with respect to the development of decision support systems. No data are available regarding possible starting points for AI-controlled interventions in resuscitation room treatment.

Objective: Do information request behavior and quality of communication indicate possible starting points for AI applications in the emergency room?

Material And Methods: A 2‑stage qualitative observational study: 1.

Hospital resource endowments and nosocomial infections: longitudinal evidence from the English National Health Service on Clostridioides difficile between 2011 and 2019.

Objectives: To identify key factors associated with Clostridioides difficile infections (CDIs) in healthcare at the hospital organization level.

Design: Longitudinal study covering the period 2011-2019. Hospital reports were analysed to determine the number of CDIs and several hospital-related environmental factors: financial resources (i.