No Cover Image

Journal article 1054 views 782 downloads

Harnessing the Power of Machine Learning in Dementia Informatics Research: Issues, Opportunities and Challenges

Gavin Tsang, Xianghua Xie Orcid Logo, Shangming Zhou, Shang-ming Zhou Orcid Logo

IEEE Reviews in Biomedical Engineering, Pages: 1 - 1

Swansea University Authors: Xianghua Xie Orcid Logo, Shang-ming Zhou Orcid Logo

Abstract

Dementia is a chronic and degenerative condition affecting millions globally. The care of patients with dementia presents an ever continuing challenge to healthcare systems in the 21st century. Medical and health sciences have generated unprecedented volumes of data related to health and wellbeing f...

Full description

Published in: IEEE Reviews in Biomedical Engineering
ISSN: 1937-3333 1941-1189
Published: IEEE 2019
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa49119
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Dementia is a chronic and degenerative condition affecting millions globally. The care of patients with dementia presents an ever continuing challenge to healthcare systems in the 21st century. Medical and health sciences have generated unprecedented volumes of data related to health and wellbeing for patients with dementia due to advances in information technology, such as genetics, neuroimaging, cognitive assessment, free texts, routine electronic health records etc. Making the best use of these diverse and strategic resources will lead to high quality care of patients with dementia. As such, machine learning becomes a crucial factor in achieving this objective. The aim of this paper is to provide a state-of-the-art review of machine learning methods applied to health informatics for dementia care. We collate and review the existing scientific methodologies and identify the relevant issues and challenges when faced with big health data. Machine learning has demonstrated promising applications to neuroimaging data analysis for dementia care, while relatively less efforts have been made to make use of integrated heterogeneous data via advanced machine learning approaches. We further indicate the future potentials and research directions of applying advanced machine learning, such as deep learning, to dementia informatics.
College: Faculty of Science and Engineering
Start Page: 1
End Page: 1