Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph

In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical resources and provide treatment programs. The techniqu...

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Autores principales:	Wanheng Liu, Ling Yin, Cong Wang, Fulin Liu, Zhiyu Ni
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Medicine (General) R5-920 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/4dd95ffd3fe349d7aba80e31b88aa2d0
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spelling	oai:doaj.org-article:4dd95ffd3fe349d7aba80e31b88aa2d02021-11-15T01:19:29ZMultitask Healthcare Management Recommendation System Leveraging Knowledge Graph2040-230910.1155/2021/1233483https://doaj.org/article/4dd95ffd3fe349d7aba80e31b88aa2d02021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1233483https://doaj.org/toc/2040-2309In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical resources and provide treatment programs. The technique we applied is referred to as KG-based recommendation system. When several experiments have been carried out, it is demonstrated that it is more intelligent and precise in disease prediction and treatment recommendation, similar to the state of the art. Also, it works well in the accuracy and comprehension, which is much higher and highly consistent with the predictions of the theoretical model. The fact that our work involves studies of multitask healthcare management recommendation system, which can contribute to the smart healthcare development, proves to be promising and encouraging.Wanheng LiuLing YinCong WangFulin LiuZhiyu NiHindawi LimitedarticleMedicine (General)R5-920Medical technologyR855-855.5ENJournal of Healthcare Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920 Medical technology R855-855.5
spellingShingle	Medicine (General) R5-920 Medical technology R855-855.5 Wanheng Liu Ling Yin Cong Wang Fulin Liu Zhiyu Ni Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
description	In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical resources and provide treatment programs. The technique we applied is referred to as KG-based recommendation system. When several experiments have been carried out, it is demonstrated that it is more intelligent and precise in disease prediction and treatment recommendation, similar to the state of the art. Also, it works well in the accuracy and comprehension, which is much higher and highly consistent with the predictions of the theoretical model. The fact that our work involves studies of multitask healthcare management recommendation system, which can contribute to the smart healthcare development, proves to be promising and encouraging.
format	article
author	Wanheng Liu Ling Yin Cong Wang Fulin Liu Zhiyu Ni
author_facet	Wanheng Liu Ling Yin Cong Wang Fulin Liu Zhiyu Ni
author_sort	Wanheng Liu
title	Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
title_short	Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
title_full	Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
title_fullStr	Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
title_full_unstemmed	Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
title_sort	multitask healthcare management recommendation system leveraging knowledge graph
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/4dd95ffd3fe349d7aba80e31b88aa2d0
work_keys_str_mv	AT wanhengliu multitaskhealthcaremanagementrecommendationsystemleveragingknowledgegraph AT lingyin multitaskhealthcaremanagementrecommendationsystemleveragingknowledgegraph AT congwang multitaskhealthcaremanagementrecommendationsystemleveragingknowledgegraph AT fulinliu multitaskhealthcaremanagementrecommendationsystemleveragingknowledgegraph AT zhiyuni multitaskhealthcaremanagementrecommendationsystemleveragingknowledgegraph
_version_	1718428920778326016

Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph

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