Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods

: Currently, advances in technology have permitted increases in the life expectancy of older adults. As a result, a large segment of the world population is 60’s years old, and over. Depression is an important disease in older adults is depression, which seriously affects the moods and behavior of e...

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Main Authors:	Alicia Martínez, Richard Benítez, Hugo Estrada, Yasmín Hernández
Format:	Article
Language:	English
Published:	MDPI AG 2018-10-01
Series:	Proceedings
Subjects:	depression fuzzy rules older adults predictive model
Online Access:	http://www.mdpi.com/2504-3900/2/19/551

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spelling	doaj-0769dca5e54c42cea492824bde1adc792020-11-24T20:40:37ZengMDPI AGProceedings2504-39002018-10-0121955110.3390/proceedings2190551proceedings2190551Predictive Model for Detection of Depression Based on Uncertainty Analysis MethodsAlicia Martínez0Richard Benítez1Hugo Estrada2Yasmín Hernández3National Institute of Technology of Mexico/CENIDET, Cuernavaca, Morelos 62490, MexicoNational Institute of Technology of Mexico/CENIDET, Cuernavaca, Morelos 62490, MexicoINFOTEC Center for Research and Innovation in Information Technology and Communications, Mexico City 14050, MexicoNational Institute of Electricity and Clean Energy, Information Technology Management, Cuernavaca, Morelos 62490, Mexico: Currently, advances in technology have permitted increases in the life expectancy of older adults. As a result, a large segment of the world population is 60’s years old, and over. Depression is an important disease in older adults is depression, which seriously affects the moods and behavior of elderly. Novel technologies for smart cities allow us to monitor people and prevent problematic situations related to this mental illness. In this paper, we propose a predictive model to automatically detect depression in older adults. The model is based on machine-learning techniques to analyze the data obtained by a sensor that monitores the daily activities of older adults. Also, the model was evaluated obtaining promising results.http://www.mdpi.com/2504-3900/2/19/551depressionfuzzy rulesolder adultspredictive model
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Alicia Martínez Richard Benítez Hugo Estrada Yasmín Hernández
spellingShingle	Alicia Martínez Richard Benítez Hugo Estrada Yasmín Hernández Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods Proceedings depression fuzzy rules older adults predictive model
author_facet	Alicia Martínez Richard Benítez Hugo Estrada Yasmín Hernández
author_sort	Alicia Martínez
title	Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods
title_short	Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods
title_full	Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods
title_fullStr	Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods
title_full_unstemmed	Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods
title_sort	predictive model for detection of depression based on uncertainty analysis methods
publisher	MDPI AG
series	Proceedings
issn	2504-3900
publishDate	2018-10-01
description	: Currently, advances in technology have permitted increases in the life expectancy of older adults. As a result, a large segment of the world population is 60’s years old, and over. Depression is an important disease in older adults is depression, which seriously affects the moods and behavior of elderly. Novel technologies for smart cities allow us to monitor people and prevent problematic situations related to this mental illness. In this paper, we propose a predictive model to automatically detect depression in older adults. The model is based on machine-learning techniques to analyze the data obtained by a sensor that monitores the daily activities of older adults. Also, the model was evaluated obtaining promising results.
topic	depression fuzzy rules older adults predictive model
url	http://www.mdpi.com/2504-3900/2/19/551
work_keys_str_mv	AT aliciamartinez predictivemodelfordetectionofdepressionbasedonuncertaintyanalysismethods AT richardbenitez predictivemodelfordetectionofdepressionbasedonuncertaintyanalysismethods AT hugoestrada predictivemodelfordetectionofdepressionbasedonuncertaintyanalysismethods AT yasminhernandez predictivemodelfordetectionofdepressionbasedonuncertaintyanalysismethods
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Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods

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