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

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Title: Using Patient Information for the Prediction of Caregiver Burden in Amyotrophic Lateral Sclerosis
Authors: Antoniadi, Anna MarkellaGalvin, MiriamHeverin, MarkHardiman, OrlaMooney, Catherine
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Date: 21-Sep-2020
Online since: 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.
Funding Details: European Commission - European Regional Development Fund
Health Research Board
Science Foundation Ireland
Funding Details: FutureNeuro
American ALS Association
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2020 the Authors
Keywords: Amyotrophic lateral sclerosisMachine learningRandom forestCaregiver burden
DOI: 10.1145/3388440.3414908
Language: en
Status of Item: Peer reviewed
Is part of: 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:
Appears in Collections:Computer Science Research Collection

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