Will we trust AI to reduce Emergency Department overcrowding?

Anton Cush

doi:10.29086/JISfTeH.10.e7

Will we trust AI to reduce Emergency Department overcrowding?

Anton Cush pre PhD at The University of Queensland

DOI: https://doi.org/10.29086/JISfTeH.10.e7

Keywords: digital health, emergency department, artificial intelligence

Abstract

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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

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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

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Issue

Vol 10 (2022)

Section

Letters

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