Forecasting emergency department occupancy with advanced machine learning models and multivariable input

Author:

Tuominen JalmariORCID,Pulkkinen EetuORCID,Peltonen Jaakko,Kanniainen JuhoORCID,Oksala NikuORCID,Palomäki Ari,Roine Antti

Publisher

Elsevier BV

Subject

Business and International Management

Reference46 articles.

1. Akiba, Takuya, Sano, Shotaro, Yanase, Toshihiko, Ohta, Takeru, & Koyama, Masanori (2019). Optuna: A next-generation hyperparameter optimization framework. In Proceedings of the ACM SIGKDD international conference on knowledge discovery and data mining (pp. 2623–2631).

2. A conceptual model of emergency department crowding;Asplin;Annals of Emergency Medicine,2003

3. Associations between crowding and ten-day mortality among patients allocated lower triage acuity levels without need of acute hospital care on departure from the emergency department;Berg;Annals of Emergency Medicine,2019

4. Bergstra, James, Bardenet, Rémi, Bengio, Yoshua, & Kégl, Balázs (2011). Algorithms for hyper-parameter optimization. In Advances in neural information processing systems 24: 25th annual conference on neural information processing systems 2011 NIPS 2011, (pp. 1–9). ISBN: 9781618395993.

5. Emergency department crowding: Time for interventions and policy evaluations;Boyle;Emergency Medicine International,2012

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