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Use of Machine Learning in Hospital Emergency Care for Patients

  • Ogosi Auqui José Antonio
  • , Sigarrostegui Gutiérrez Juan Enrique
  • , Piscoya Ángeles Patricia Noemí
  • , Yucra Sotomayor Daniel Alejandro
  • , Sotomayor Abarca Julio Elmer
  • , Petrlik Azabache Iván Carlo
  • Universidad Nacional Federico Villarreal
  • Universidad Privada del Norte
  • Universidad Científica del Sur

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of the 22nd LACCEI International Multi-Conference for Engineering, Education and Technology
Subtitle of host publicationSustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0., LACCEI 2024
ISBN (Electronic)9786289520781
DOIs
StatePublished - 2024
Event22nd LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2024 - Hybrid, San Jose, Costa Rica
Duration: 17 Jul 202419 Jul 2024

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
ISSN (Electronic)2414-6390

Conference

Conference22nd LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2024
Country/TerritoryCosta Rica
CityHybrid, San Jose
Period17/07/2419/07/24

Keywords

  • artificial intelligence
  • hospital emergency
  • Machine learning
  • medical care
  • process of care

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