Izvorni znanstveni članak

https://doi.org/10.20471/acc.2023.62.01.16

Optimization of Pre-Hospital First Aid Management Strategies for Patients with Infectious Diseases in Huizhou City using Deep Learning Algorithm

Jing Zeng ; Department of Emergency, Huizhou Third People’s Hospital, Guangzhou Medical University, Huizhou, China
WeiSheng Chen ; Department of Emergency Intensive Care Unit, Huizhou Third People’s Hospital, Guangzhou Medical University, Huizhou, China
WeiWei Chen ; Department of Emergency, Huizhou Third People’s Hospital, Guangzhou Medical University, Huizhou, China
YaWei Wang ; Department of Emergency, Huizhou Third People’s Hospital, Guangzhou Medical University, Huizhou, China
XueSong Li ; Center for Neuromedicine, Huizhou Third People’s Hospital, Guangzhou Medical University, Huizhou, Guangdong Province, China

Sažetak

The aim of the study was to optimize the pre-hospital first aid management strategy
for patients with infectious diseases in Huizhou city, which is expected to provide a basis for the
epidemic prevention and control, to save lives, and increase the pre-hospital first aid efficiency. At the
Department of Emergency, Huizhou Third People’s Hospital as the research subject, the common
pre-hospital first aid procedure for infectious diseases was identified. The Petri net was used to model
and determine the execution time of each link of the pre-hospital first aid process. The isomorphic
Markov chain was used to optimize the pre-hospital first aid procedure for infectious diseases. In
terms of the emergency path, deep learning was combined with the reinforcement learning model
to construct the reinforcement learning model for ambulance path planning. Isomorphic Markov
chain analysis revealed that the patient status when returning to the hospital, the time needed for the
ambulance to come to designated location, and the on-site treatment were the main problems in the
first aid process, and the time needed for the pre-hospital first aid process was reduced by 25.17% after
optimization. In conclusion, Petri net and isomorphic Markov chain can optimize the pre-hospital
first aid management strategies for patients with infectious diseases, and the use of deep learning algorithm
can effectively plan the emergency path, achieving intelligent and informationalized pre-hospital
transfer, which provides a basis for reducing the suffering, mortality, and disability rate of patients
with infectious diseases.

Ključne riječi

Petri net; Isomorphic Markov chain; Infectious disease; Deep learning; Enhanced learning; Path planning

Hrčak ID:

307271

URI

https://hrcak.srce.hr/307271

Datum izdavanja:

1.4.2023.

Podaci na drugim jezicima: hrvatski

Posjeta: 308 *