English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Predicting patient volumes in a hospital setting is a well-studiedapplication of time series forecasting. Existing tools usually make forecastsat the daily or weekly level to assist in planning for staffing requirements.Prompted by new COVID-related capacity constraints placed on our pediatrichospital's emergency department, we developed an hourly forecasting tool tomake predictions over a 24 hour window. These forecasts would give our hospitalsufficient time to be able to martial resources towards expanding capacity andaugmenting staff (e.g. transforming wards or bringing in physicians on call).Using Gaussian Process Regressions (GPRs), we obtain strong performance forboth point predictions (average R-squared: 82%) as well as classificationaccuracy when predicting the ordinal tiers of our hospital's capacity (averageprecision/recall: 82%/74%). Compared to traditional regression approaches, GPRsnot only obtain consistently higher performance, but are also robust to thedataset shifts that have occurred throughout 2020. Hospital stakeholders areencouraged by the strength of our results, and we are currently working onmoving our tool to a real-time setting with the goal of augmenting thecapabilities of our healthcare workers.

Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds