Towards an understanding classification of well-being for care of older people

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Cufoglu, Ayse and Chin, Jeannette ORCID: https://orcid.org/0000-0002-9398-5579 (2015) Towards an understanding classification of well-being for care of older people. In: 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), 2015-07-22 - 2015-07-24.

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Abstract

As the ageing population increases, more and more people require care and support. To date there has been limited understanding of older people?s needs and the general well- being when they are in care. In this paper we investigated the relationships between the indices of independence in daily activities of the people who are in care and the behaviour rating scale [2] defined in the nursing assessment in connection with the indices to predetermine individuals? well-being during their stay. For this study, we focus on three well-being attributes, Cognition, Social Relations and Communications which are important for understanding the people in care. The study is based on a set of datasets consists of 40,000 records. The datasets were trained, tested and analysed using four Machine Learning (ML) classifications algorithms that are Bayesian Networks (BN), Nai?ve Bayesian (NB), Nai?ve Bayesian Tree (NBTree) and Instance Based Learner (IBL). The results show that Bayesian based algorithms performs very good with well-being data with respect to determining the relationship between the daily activities and the behavior rating scale, to predetermine the needs and well- being of the people who are in care.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	array(0x7feaf0e41e38)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://arro.anglia.ac.uk/700865/
Depositing User:	LivePure Connector
Date Deposited:	27 Jun 2019 07:30
Last Modified:	24 Sep 2024 07:22
URI:	https://ueaeprints.uea.ac.uk/id/eprint/71557
DOI:	10.1109/INDIN.2015.7281954

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