Early adoption of telehealth/remote patient monitoring and hospital revenue changes during COVID-19.

Introduction: The COVID-19 pandemic dramatically affected the financial performance of hospitals across the U.S. The prompt availability of telehealth options likely impacted both a hospital's healthcare options and opportunities for revenue in the short-term.

Fixational eye movements enhance the precision of visual information transmitted by the primate retina.

Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the retinal signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of retinal ganglion cells (RGCs) in the macaque retina (male), combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provides an interpretable framework for characterizing the retinal signal.

Rural Hospital Service Lines: Changes Over Time and Impacts on Profitability.

Goal: To document shifts in rural hospital service line offerings between 2010 and 2021 and to assess the resulting impacts on hospital profitability.

Methods: We used annual Medicare cost report data for all rural hospitals that did not change payment classifications between 2010 and 2021. We documented changes in the percentages of hospitals offering each of the 37 inpatient or ancillary service lines included in the data.

Modeling responses of macaque and human retinal ganglion cells to natural images using a convolutional neural network.

Linear-nonlinear (LN) cascade models provide a simple way to capture retinal ganglion cell (RGC) responses to artificial stimuli such as white noise, but their ability to model responses to natural images is limited. Recently, convolutional neural network (CNN) models have been shown to produce light response predictions that were substantially more accurate than those of a LN model. However, this modeling approach has not yet been applied to responses of macaque or human RGCs to natural images.