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  5. Using Patient Information for the Prediction of Caregiver Burden in Amyotrophic Lateral Sclerosis
 
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Using Patient Information for the Prediction of Caregiver Burden in Amyotrophic Lateral Sclerosis

Author(s)
Antoniadi, Anna Markella  
Galvin, Miriam  
Heverin, Mark  
Hardiman, Orla  
Mooney, Catherine  
Uri
http://hdl.handle.net/10197/12180
Date Issued
2020-09-21
Date Available
2021-05-19T16:36:41Z
Abstract
The aim of this study is to create a Clinical Decision Support System (CDSS) to assist in the early identification and support of caregivers at risk of experiencing burden while caring for a person with Amyotrophic Lateral Sclerosis. We work towards a system that uses a minimum amount of data that could be routinely collected. We investigated if the impairment of patients alone provides sufficient information for the prediction of caregiver burden. Results reveal a better performance of our system in identifying those at risk of high burden, but more information is needed for an accurate CDSS.
Sponsorship
European Commission - European Regional Development Fund
Health Research Board
Science Foundation Ireland
Other Sponsorship
FutureNeuro
American ALS Association
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2020 the Authors
Subjects

Amyotrophic lateral s...

Machine learning

Random forest

Caregiver burden

DOI
10.1145/3388440.3414908
Language
English
Status of Item
Peer reviewed
Journal
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
ISBN
9781450379649
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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SIGBio_poster_2020_Anna.pdf

Size

286.86 KB

Format

Adobe PDF

Checksum (MD5)

be1b5d816799785fcfca2b92a292e7e7

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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