A neural-network-based model for the removal of biomedical equipment from a hospital inventory

This article puts forward an accurate and robust model based on a artificial neural network that guarantees a warning when a piece of medical equipment requires replacement. A perceptron neural network composed by one input layer with two neurons is described. The artificial neural network can class...

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Autores Principales: Cruz, Antonio Miguel, Rodríguez, Denis Ernesto
Formato: Artículo (Article)
Lenguaje:Inglés (English)
Publicado: Wolters Kluwer Health 2006
Materias:
Acceso en línea:https://repository.urosario.edu.co/handle/10336/27609
id ir-10336-27609
recordtype dspace
spelling ir-10336-276092020-08-19T14:47:02Z A neural-network-based model for the removal of biomedical equipment from a hospital inventory Un modelo basado en redes neuronales para la eliminación de equipos biomédicos del inventario de un hospital Cruz, Antonio Miguel Rodríguez, Denis Ernesto Artificial neural network Groups This article puts forward an accurate and robust model based on a artificial neural network that guarantees a warning when a piece of medical equipment requires replacement. A perceptron neural network composed by one input layer with two neurons is described. The artificial neural network can classify data in groups. In this research three groups were classified. These groups depend on numerical values of service cost/acquisition cost and usage time/useful life time ratios. A supervised learning rule to train the artificial neural network was selected. The training process was carried out by collecting typical data from 200 high-performance as well as 100 low-performance devices from four hospitals under study. The network was tested by collecting data (998 high-performance as well as 765 low-performance devices) in 4 hospitals. In 100 % of the cases the artificial neural network classified the equipment in the expected groups. It can be concluded that the network had a great level of data discrimination and an excellent performance level. 2006 2020-08-19T14:42:58Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion ISSN: 0363-8855 EISSN: 1550-3275 https://repository.urosario.edu.co/handle/10336/27609 eng info:eu-repo/semantics/restrictedAccess application/pdf Wolters Kluwer Health Journal of Clinical Engineering
institution EdocUR - Universidad del Rosario
collection DSpace
language Inglés (English)
topic Artificial neural network
Groups
spellingShingle Artificial neural network
Groups
Cruz, Antonio Miguel
Rodríguez, Denis Ernesto
A neural-network-based model for the removal of biomedical equipment from a hospital inventory
description This article puts forward an accurate and robust model based on a artificial neural network that guarantees a warning when a piece of medical equipment requires replacement. A perceptron neural network composed by one input layer with two neurons is described. The artificial neural network can classify data in groups. In this research three groups were classified. These groups depend on numerical values of service cost/acquisition cost and usage time/useful life time ratios. A supervised learning rule to train the artificial neural network was selected. The training process was carried out by collecting typical data from 200 high-performance as well as 100 low-performance devices from four hospitals under study. The network was tested by collecting data (998 high-performance as well as 765 low-performance devices) in 4 hospitals. In 100 % of the cases the artificial neural network classified the equipment in the expected groups. It can be concluded that the network had a great level of data discrimination and an excellent performance level.
format Artículo (Article)
author Cruz, Antonio Miguel
Rodríguez, Denis Ernesto
author_facet Cruz, Antonio Miguel
Rodríguez, Denis Ernesto
author_sort Cruz, Antonio Miguel
title A neural-network-based model for the removal of biomedical equipment from a hospital inventory
title_short A neural-network-based model for the removal of biomedical equipment from a hospital inventory
title_full A neural-network-based model for the removal of biomedical equipment from a hospital inventory
title_fullStr A neural-network-based model for the removal of biomedical equipment from a hospital inventory
title_full_unstemmed A neural-network-based model for the removal of biomedical equipment from a hospital inventory
title_sort neural-network-based model for the removal of biomedical equipment from a hospital inventory
publisher Wolters Kluwer Health
publishDate 2006
url https://repository.urosario.edu.co/handle/10336/27609
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score 12,131701