Use of Machine Learning in Hospital Emergency Care for Patients

Auqui José Antonio O.; Gutiérrez Juan Enrique S.; Ángeles Patricia Noemí P.; Sotomayor Daniel Alejandro Y.; Abarca Julio Elmer S.; Azabache Iván Carlo P. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/laccei2024.1.1.1130

Resumen

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.

Instituciones: Universidad Científica del Sur; Universidad Nacional Federico Villarreal; Universidad Privada del Norte