Use of Machine Learning in Hospital Emergency Care for Patients
DOI:
https://doi.org/10.18687/LACCEI2024.1.1.1130Keywords:
Machine learning, process of care, medical care, artificial intelligence, hospital emergency.Abstract
This paper addresses the design and implementation of a Machine Learning model in the process of patient care in hospital emergencies. With the aim of improving efficiency and quality in the provision of emergency medical services, the application of advanced machine learning techniques is proposed. The central problem lies in optimizing the triage process and the assignment of priorities, crucial aspects in the emergency field. The research is framed within a descriptive and applied approach, using observation as the main data collection technique. The observation sheet, structured on the basis of specific indicators, serves as an instrument to evaluate the performance of the model in practical situations. The main objective of this approach is the effective integration of Machine Learning technology into the workflow of hospital emergency departments, with a view to improving decision-making, resource allocation and, ultimately, patient care.Downloads
Published
2024-07-27
Issue
Section
Articles
Copyright
Copyright (c) 2024 LACCEI
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
LACCEI retains copyright of all published articles under the terms of its copyright transfer agreement. As the copyright holder, LACCEI distributes the articles to the public under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
How to Cite
Ogosi Auqui, J. A., Sigarrostegui Gutierrez, J. E., Piscoya Ángeles, P. N., Yucra Sotomayor, D. A., Sotomayor Abarca, J. E., & Petrlik Azabache, I. C. (2024). Use of Machine Learning in Hospital Emergency Care for Patients. LACCEI, 1(10). https://doi.org/10.18687/LACCEI2024.1.1.1130