Unsupervised machine learning of integrated health and
social care data from the Macmillan Improving the Cancer
Journey service in Glasgow

Kang, Kean Lee; Greer, Margaret; Brown, James; Preston, Janice; Mabelis, Judith; Hepburn, Leigh-Anne; Fisher, Miriam; Falconer, Ruth; McDermott, Sandra; Deed, Stuart

Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow

Output Details

Kang, Kean Lee, Greer, Margaret, Brown, James, Preston, Janice, Mabelis, Judith, Hepburn, Leigh-Anne, Fisher, Miriam, Falconer, Ruth, McDermott, Sandra and Deed, Stuart (2018) Unsupervised machine learning of integrated health and social care data from the Macmillan Improving the Cancer Journey service in Glasgow. British Journal of Cancer, 119. pp. 3-4. ISSN 0007-0920
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Unsupervised machine learning of integrated health and
social care data from the Macmillan Improving the Cancer
Journey service in Glasgow

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Further Details

Creators/Authors:

Kang, Kean Lee, Greer, Margaret, Brown, James, Preston, Janice, Mabelis, Judith, Hepburn, Leigh-Anne, Fisher, Miriam, Falconer, Ruth, McDermott, Sandra and Deed, Stuart

Abstract:

Improving the Cancer Journey (ICJ) was launched in
2014 by Glasgow City Council and Macmillan Cancer Support. As
part of routine service, data is collected on ICJ users including
demographic and health information, results from holistic needs
assessments and quality of life scores as measured by EQ-5D
health status. There is also data on the number and type of
referrals made and feedback from users on the overall service. By
applying artificial intelligence and interactive visualization technologies to this data, we seek to improve service provision and
optimize resource allocation.

Official URL:

https://www.nature.com/articles/s41416-018-0299-z.pdf

Uncontrolled Keywords:

Cancer; Journeys; Health; Care; Data

School/Academic Area:

School of Innovation and Technology

Dates:

Date

Date Type

8 November 2018

Published Online

Status: