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.
Artículo
en Chino
| WPRIM
| ID: wpr-922063
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Autoimagen
/
Equipo Quirúrgico
/
Algoritmos
/
Simulación por Computador
/
Aprendizaje Automático
Tipo de estudio:
Estudio pronóstico
Idioma:
Chino
Revista:
Chinese Journal of Medical Instrumentation
Año:
2021
Tipo del documento:
Artículo
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