preprint · Research Square
Abstract Efficiency is crucial, in Emergency Departments (EDs). It can be hindered by the number of patients. In this study we present a solution that utilizes the increasing amount of healthcare data and advancements in data analysis techniques. Our approach involves a combination of LSTM and Decision Tree models to enhance the accuracy of predicting volume, in EDs. The results indicate that our model outperforms existing methods suggesting its potential to improve ED efficiency.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.21203/rs.3.rs-3195031/v1
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
