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

Content Provider	IEEE Xplore Digital Library
Author	Cufoglu, A. Chin, J.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. & Technol., Anglia Ruskin Univ., Cambridge, UK (Cufoglu, A.; Chin, J.)
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), Naïve Bayesian (NB), Naïve 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.
Starting Page	1494
Ending Page	1499
File Size	534115
Page Count	6
File Format	PDF
e-ISBN	9781479966493
DOI	10.1109/INDIN.2015.7281954
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-22
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	well-being Machine learning algorithms Classifications elderly Medical services long-term care Cognition personalisations Classification algorithms Machine Learning Niobium Accuracy aging population NHS Bayes methods nursing care care homes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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