This paper is in the following e-collection/theme issue:

Machine Learning (1465) Natural Language Processing (693) Electronic Health Records (1053) Decision Support for Health Professionals (1185)

Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39892, first published .
Effect of Applying a Real-Time Medical Record Input Assistance System With Voice Artificial Intelligence on Triage Task Performance in the Emergency Department: Prospective Interventional Study

Effect of Applying a Real-Time Medical Record Input Assistance System With Voice Artificial Intelligence on Triage Task Performance in the Emergency Department: Prospective Interventional Study

Effect of Applying a Real-Time Medical Record Input Assistance System With Voice Artificial Intelligence on Triage Task Performance in the Emergency Department: Prospective Interventional Study

Authors of this article:

Ara Cho1 Author Orcid Image ;   In Kyung Min2 Author Orcid Image ;   Seungkyun Hong3 Author Orcid Image ;   Hyun Soo Chung1 Author Orcid Image ;   Hyun Sim Lee4 Author Orcid Image ;   Ji Hoon Kim1 Author Orcid Image
Article Authors Cited by (9) Tweetations (5) Metrics

Journals

  1. Kim J. Data integration using information and communication technology for emergency medical services and systems. Clinical and Experimental Emergency Medicine 2023;10(2):129 View
  2. Martinez-Ortigosa A, Martinez-Granados A, Gil-Hernández E, Rodriguez-Arrastia M, Ropero-Padilla C, Roman P, Leal-Costa C. Applications of Artificial Intelligence in Nursing Care: A Systematic Review. Journal of Nursing Management 2023;2023:1 View
  3. De Rosario H, Pitarch-Corresa S, Pedrosa I, Vidal-Pedrós M, de Otto-López B, García-Mieres H, Álvarez-Rodríguez L. Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review. JMIR Medical Informatics 2023;11:e48693 View
  4. Charan G, Charan A, Khurana M, Narang G. Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit: A Narrative Review. Galician Medical Journal 2023;30(4) View
  5. Lee S, Lee J, Park J, Park J, Kim D, Lee J, Oh J. Deep learning-based natural language processing for detecting medical symptoms and histories in emergency patient triage. The American Journal of Emergency Medicine 2024;77:29 View
  6. Ruksakulpiwat S, Thorngthip S, Niyomyart A, Benjasirisan C, Phianhasin L, Aldossary H, Ahmed B, Samai T. A Systematic Review of the Application of Artificial Intelligence in Nursing Care: Where are We, and What’s Next?. Journal of Multidisciplinary Healthcare 2024;Volume 17:1603 View
  7. Jiang M, Guo L, Li S, Xiao X, Chen W, Chen S, Chen N, Sun Y, Zhang G, Zeng X, Xiao Y, Fan L. IVF laboratory management through workflow-based RFID tag witnessing and real-time information entry. Reproductive Biology and Endocrinology 2024;22(1) View
  8. Al Khatib I, Ndiaye M. Artificial Intelligence role in changing the role of nurses in patient care: Systematic Review (Preprint). JMIR Nursing 2024 View
  9. Yi N, Baik D, Baek G. The effects of applying artificial intelligence to triage in the emergency department: A systematic review of prospective studies. Journal of Nursing Scholarship 2024 View