Will we trust AI to reduce Emergency Department overcrowding?

  • Anton Cush pre PhD at The University of Queensland
Keywords: digital health, emergency department, artificial intelligence

Abstract

    

References

Morley C, Unwin M, Peterson GM, Stankovich J, Kinsman, L. Emergency department crowding: A systematic review of causes, consequences and solutions. PLOS ONE 2018;13(8), p.e0203316. DOI: https://doi.org/10.1371/journal.pone.0203316

Dicuonzo G, Donofrio, F, Fusco, Shini M. Healthcare system: Moving forward with artificial intelligence. Technovation 2022;p.102510. DOI: https://doi.org/10.1016/j.technovation.2022.102510

Siala H, Wang Y. SHIFTing artificial intelligence to be responsible in healthcare: A systematic review", Social Science & Amp. Medicine (2022);, p. 114782. DOI: https://doi.org/10.1016/j.socscimed.2022.114782

Mohanty, S. et al. Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare. Patterns 2022;3(1): p.100395. DOI: https://doi.org/10.1016/j.patter.2021.100395

Published
2022-12-28
How to Cite
Cush, A. (2022). Will we trust AI to reduce Emergency Department overcrowding?. Journal of the International Society for Telemedicine and EHealth, 10, e7 (1). https://doi.org/10.29086/JISfTeH.10.e7
Section
Letters