Using stochastic simulation modelling to study occupancy levels of decentralised admission avoidance units in Norway.

Identifying alternatives to acute hospital admission is a priority for many countries. Over 200 decentralised municipal acute units (MAUs) were established in Norway to divert low-acuity patients away from hospitals. MAUs have faced criticism for low mean occupancy and not relieving pressures on hospitals.

Reconstructing the exit wave of 2D materials in high-resolution transmission electron microscopy using machine learning.

Reconstruction of the exit wave function is an important route to interpreting high-resolution transmission electron microscopy (HRTEM) images. Here we demonstrate that convolutional neural networks can be used to reconstruct the exit wave from a short focal series of HRTEM images, with a fidelity comparable to conventional exit wave reconstruction. We use a fully convolutional neural network based on the U-Net architecture, and demonstrate that we can train it on simulated exit waves and simulated HRTEM images of graphene-supported molybdenum disulphide (an industrial desulfurization catalyst).

Prediction of occult atrial fibrillation in patients after cryptogenic stroke and transient ischaemic attack: PROACTIA.

Aims: Studies with implantable cardiac monitors (ICMs) show that one-third of patients with cryptogenic stroke/transient ischaemic attack (TIA) have episodes of subclinical atrial fibrillation (SCAF) and benefit switching from antiplatelet- to anticoagulant therapy. However, ICMs are costly and resource demanding. We aimed to build a score based on participant's baseline characteristics that could assess individual risk of SCAF.

Stroke unit demand in Norway - present and future estimates.

Background: All stroke patients should receive timely admission to a stroke unit (SU). Consequently, most patients with suspected strokes - including stroke mimics (SM) are admitted. The aim of this study was to estimate the current total demand for SU bed capacity today and give estimates for future (2020-2040) demand.

Stroke Mimics on the Stroke Unit - Temporal trends 2008-2017 at a large Norwegian university hospital.

Objectives: The objective was to quantify temporal trends in stroke mimics (SM) admissions relative to cerebrovascular accidents (CVA), incidence of hospitalized SMs and characterize the SM case-mix at a general hospital's stroke unit (SU).

Materials & Methods: All SU admissions (n = 11240) of patients aged 15 or older to Haukeland University Hospital between 2008-2017 were prospectively included and categorized as CVA or SM. Logistic regression was used to estimate time trends in the proportion of SMs among the admissions.