A Deep Learning-Based Text Classification of Adverse Nursing Events

Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient’s diagnosis and treatment results and even increase the patient’s pain and burden. Additionally, It is high li...

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Autores principales:	Wenjing Lu, Wei Jiang, Na Zhang, Feng Xue
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/f943cbd6bafb470f839267a9754f5d58
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spelling	oai:doaj.org-article:f943cbd6bafb470f839267a9754f5d582021-11-29T00:56:46ZA Deep Learning-Based Text Classification of Adverse Nursing Events2040-230910.1155/2021/9800114https://doaj.org/article/f943cbd6bafb470f839267a9754f5d582021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9800114https://doaj.org/toc/2040-2309Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient’s diagnosis and treatment results and even increase the patient’s pain and burden. Additionally, It is high likely to cause accidents and disputes and affect normal medical work and personnel safety and is not conducive to the development of the health system. Due to the rapid development of modern medicine, health and safety of patients have become the most concerned issue in society and patient safety is an important part of medical care management. Research and events have shown that classified management of adverse nursing events, event analysis, and improvement measures are beneficial, specifically to the health system, to continuously improve the quality of medical care and reduce the occurrence of adverse nursing events. In the management of adverse nursing events, it is very important to categorize the text reports of adverse nursing events and divide these into different categories and levels. Traditional reports of adverse nursing events are mostly unstructured and simple data, often relying on manual classification, which is difficult to analyze. Furthermore, data is relatively inaccurate and practical reference significance is not obvious. In this paper, we have extensively evaluated various deep learning-based classification methods which are specifically designed for the healthcare systems. It becomes possible with the development of science and technology; text classification methods based on deep learning are gradually entering people’s field of vision. Additionally, we have proposed a text classification model for adverse nursing events in the health system. Experiments and data comparison test of both the proposed deep learning-based method and existing methods in the text classification of nursing adverse events effect are performed. These results show the exceptional performance of the proposed mechanism in terms of various evaluation metrics.Wenjing LuWei JiangNa ZhangFeng XueHindawi 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 Wenjing Lu Wei Jiang Na Zhang Feng Xue A Deep Learning-Based Text Classification of Adverse Nursing Events
description	Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient’s diagnosis and treatment results and even increase the patient’s pain and burden. Additionally, It is high likely to cause accidents and disputes and affect normal medical work and personnel safety and is not conducive to the development of the health system. Due to the rapid development of modern medicine, health and safety of patients have become the most concerned issue in society and patient safety is an important part of medical care management. Research and events have shown that classified management of adverse nursing events, event analysis, and improvement measures are beneficial, specifically to the health system, to continuously improve the quality of medical care and reduce the occurrence of adverse nursing events. In the management of adverse nursing events, it is very important to categorize the text reports of adverse nursing events and divide these into different categories and levels. Traditional reports of adverse nursing events are mostly unstructured and simple data, often relying on manual classification, which is difficult to analyze. Furthermore, data is relatively inaccurate and practical reference significance is not obvious. In this paper, we have extensively evaluated various deep learning-based classification methods which are specifically designed for the healthcare systems. It becomes possible with the development of science and technology; text classification methods based on deep learning are gradually entering people’s field of vision. Additionally, we have proposed a text classification model for adverse nursing events in the health system. Experiments and data comparison test of both the proposed deep learning-based method and existing methods in the text classification of nursing adverse events effect are performed. These results show the exceptional performance of the proposed mechanism in terms of various evaluation metrics.
format	article
author	Wenjing Lu Wei Jiang Na Zhang Feng Xue
author_facet	Wenjing Lu Wei Jiang Na Zhang Feng Xue
author_sort	Wenjing Lu
title	A Deep Learning-Based Text Classification of Adverse Nursing Events
title_short	A Deep Learning-Based Text Classification of Adverse Nursing Events
title_full	A Deep Learning-Based Text Classification of Adverse Nursing Events
title_fullStr	A Deep Learning-Based Text Classification of Adverse Nursing Events
title_full_unstemmed	A Deep Learning-Based Text Classification of Adverse Nursing Events
title_sort	deep learning-based text classification of adverse nursing events
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/f943cbd6bafb470f839267a9754f5d58
work_keys_str_mv	AT wenjinglu adeeplearningbasedtextclassificationofadversenursingevents AT weijiang adeeplearningbasedtextclassificationofadversenursingevents AT nazhang adeeplearningbasedtextclassificationofadversenursingevents AT fengxue adeeplearningbasedtextclassificationofadversenursingevents AT wenjinglu deeplearningbasedtextclassificationofadversenursingevents AT weijiang deeplearningbasedtextclassificationofadversenursingevents AT nazhang deeplearningbasedtextclassificationofadversenursingevents AT fengxue deeplearningbasedtextclassificationofadversenursingevents
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A Deep Learning-Based Text Classification of Adverse Nursing Events

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