Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses
Conference paper
Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. 2014. Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Orlando, FL., USA 09 - 12 Dec 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 304-309 https://doi.org/10.1109/CIDM.2014.7008682
Type | Conference paper |
---|---|
Title | Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses |
Authors | Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. |
Abstract | Survey questionnaires are often heterogeneous because they contain both quantitative (numeric) and qualitative (text) responses, as well as missing values. While traditional, model-based methods are commonly used by clinicians, we deploy Self Organizing Maps (SOM) as a means to visualise the data. In a survey study aiming at understanding the self-care behaviour of 611 patients with Type-1 Diabetes, we show that SOM can be used to (1) identify co-morbidities; (2) to link self-care factors that are dependent on each other; and (3) to visualise individual patient profiles; In evaluation with clinicians and experts in Type-1 Diabetes, the knowledge and insights extracted using SOM correspond well to clinical expectation. Furthermore, the output of SOM in the form of a U-matrix is found to offer an interesting alternative means of visualising patient profiles instead of a usual tabular form. |
Conference | 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) |
Page range | 304-309 |
ISBN | |
Hardcover | 9781479945191 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication dates | |
Dec 2014 | |
Publication process dates | |
Deposited | 22 Apr 2016 |
Accepted | 04 Jun 2014 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/CIDM.2014.7008682 |
Scopus EID | 2-s2.0-84925061166 |
Language | English |
Book title | 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) |
https://repository.mdx.ac.uk/item/864wx
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