medigraphic.com
ISSN 2594-3006 (Electronic)
ISSN 2007-1752 (Print)
Archivos de Medicina de Urgencia de México

2025, Number 2-3

Next >>

Arch Med Urg Mex 2025; 17 (2-3)

Artificial intelligence in emergency services: between promise and responsibility

Loria-Castellanos J, Cerón-Apipilhuasco A

Language: Spanish
References: 9
Page: 92-94
PDF size: 162.92 Kb.


Text Extraction

No abstract.


REFERENCES

  1. Piliuk K, Tomforde S. Artificial intelligence in emergency medicine.A systematic literature review. Int J Med Inf. 2023; 180:105274.

  2. Franco-Pérez AM. La Inteligencia Artificial en los servicios de urgencias.Hosp Domic. 2024;8(4):203-15.

  3. Abidi SSR, Abidi SR. Intelligent health data analytics: A convergenceof artificial intelligence and big data. Healthc ManageForum. 2019;32(4):178-82.

  4. McPake B, Dayal P, Zimmermann J, Williams GA. How can countriesrespond to the health and care workforce crisis? Insights from internationalevidence. Int J Health Plann Manage 2024;39(3):879-87.

  5. Esteva, A., Robicquet, A., Ramsundar, B., et al. A guide to deeplearning in healthcare. Nature Medicine 2019, 25(1): 24–29.

  6. Jiang, F., Jiang, Y., Zhi, H., et al. Artificial intelligence in healthcare:past, present and future. Stroke and Vascular Neurology 2017,2(4), 230–243.

  7. Topol, E. (2019). Deep Medicine: How Artificial Intelligence CanMake Healthcare Human Again. Basic Books.

  8. World Health Organization. (2021). Ethics and governance of artificialintelligence for health. WHO.

  9. Yu, K.-H., Beam, A. L., & Kohane, I. S. Artificial intelligence in healthcare.Nature Biomedical Engineering 2018; 2(10), 719–731.




2020     |     www.medigraphic.com