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Bed Occupancy

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Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach.

Computational and mathematical methods in medicine
Emergency departments (EDs) play a vital role in the whole healthcare system as they are the first point of care in hospitals for urgent and critically ill patients. Therefore, effective management of hospital's ED is crucial in improving the quality...

Recursive neural networks in hospital bed occupancy forecasting.

BMC medical informatics and decision making
BACKGROUND: Efficient planning of hospital bed usage is a necessary condition to minimize the hospital costs. In the presented work we deal with the problem of occupancy forecasting in the scale of several months, with a focus on personnel's holiday ...

Artificial Intelligence Forecasting Census and Supporting Early Decisions.

Nursing administration quarterly
Matching resources to demand is a daily challenge for hospital leadership. In interdisciplinary collaboration, nurse leaders and data scientists collaborated to develop advanced machine learning to support early proactive decisions to improve ability...

A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics.

PloS one
Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionall...

Time series forecasting of bed occupancy in mental health facilities in India using machine learning.

Scientific reports
Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in India and globally. With increasing demand for mental health services, effective resource management, ...