SciELO - Scientific Electronic Library Online

 
vol.26 issue1Linguistic-based Approach for Recognizing Implicit Language in Hate Speech: Exploratory InsightsComparative Analysis of K-Means Variants Implemented in R author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

BELLO-VALLE, Amado Scott; MARTINEZ-REBOLLAR, Alicia; SANCHEZ, Wendy  and  ESTRADA-ESQUIVEL, Hugo. A Predictive Model for Automatic Detection of Loneliness and Social Isolation using Machine Learning. Comp. y Sist. [online]. 2022, vol.26, n.1, pp.113-124.  Epub Aug 08, 2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-1-4157.

In Mexico, elderly is the group with the highest growth rate in the entire country. In 2010, the elderly represented 8.8% of the population and it is estimated that by 2050, they will represent 28% of the estimated population. This demographic change represents several challenges for current social programs that intend to maintain the independence of elderly in families and in their community. The problem of the development of emotional and psychological disorders in older adults can be associated with the prevalence of affective, cognitive, and behavioral disorders. In most cases, these medical conditions are not properly diagnosed or treated. This situation is currently a research topic of novel approaches to improve the well-being and quality of life of this segment of the population. The objective of research work presented in this paper is to develop a predictive model of loneliness and social isolation from the information obtained from the monitoring of the daily activities of an older adult.

Keywords : Predictive model; loneliness; social isolation; elderly.

        · text in English     · English ( pdf )