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Analyzing the Variations in Emergency Department Boarding and Testing the Transferability of Forecasting Models across COVID-19 Pandemic Waves in Hong Kong: Hybrid CNN-LSTM approach to quantifying building-level socioecological risk
March 22, 2024, 4:41 a.m. | Eman Leung (JC School of Public Health and Primary Care, The Chinese University of Hong Kong), Jingjing Guan (JC School of Public Health and Primary C
cs.LG updates on arXiv.org arxiv.org
Abstract: Emergency department's (ED) boarding (defined as ED waiting time greater than four hours) has been linked to poor patient outcomes and health system performance. Yet, effective forecasting models is rare before COVID-19, lacking during the peri-COVID era. Here, a hybrid convolutional neural network (CNN)-Long short-term memory (LSTM) model was applied to public-domain data sourced from Hong Kong's Hospital Authority, Department of Health, and Housing Authority. In addition, we sought to identify the phase of the …
abstract arxiv building cnn covid covid-19 covid-19 pandemic cs.lg emergency forecasting health hong kong hybrid kong lstm pandemic patient performance physics.soc-ph risk testing type waiting
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