Research on Self-perception and Active Warning Model of Medical Equipment Operation and Maintenance Status Based on Machine Learning Algorithm / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
; (6): 580-584, 2021.
Article
em Zh
| WPRIM
| ID: wpr-922063
Biblioteca responsável:
WPRO
ABSTRACT
The panoramic perception of medical equipment operation and maintenance status is the basic guarantee for the implementation of smart medical care, the machine learning algorithm-based autonomous perception and active early warning model of medical equipment operation and maintenance status is proposed. Introduce deep learning multi-dimensional perception of medical equipment multi-source heterogeneous fault data training sample characteristics to realize autonomous perception of medical equipment operation and maintenance status, introduce reinforcement learning to realize autonomous decision-making of test sample fault characteristics, and build the active early warning mechanism for medical equipment faults. Taking the equipment department of hospital as the carrier of model effectiveness verification, the effectiveness simulation of the model was carried out, the results show that the model has the advantages of comprehensive fault information perception, strong compatibility of medical equipment, high efficiency of active early warning.
Palavras-chave
Texto completo:
1
Índice:
WPRIM
Assunto principal:
Autoimagem
/
Equipamentos Cirúrgicos
/
Algoritmos
/
Simulação por Computador
/
Aprendizado de Máquina
Tipo de estudo:
Prognostic_studies
Idioma:
Zh
Revista:
Chinese Journal of Medical Instrumentation
Ano de publicação:
2021
Tipo de documento:
Article