Guest editorial: special issue on pervasive sensing and machine learning for mental health
File(s)
Accepted version
Author(s)
Lo, B
Zhang, Y
Inan, OT
Ellul, J
Type
Journal Article
Abstract
The seven papers included in this special section focus on machine learning applications for the mental health industry. Mental health is one of the major global health issues affecting substantially more people than other noncommunicable diseases. Much research has been focused on developing novel technologies for tackling this global health challenge, including the development of advanced analytical techniques based on extensive datasets and multimodal acquisition for early detection and treatment of mental illnesses. The papers in this issue are dedicated to cover the related topics on technological advancements for mental health care and diagnosis with a focus on pervasive sensing and machine learning.
Date Issued
2019-11-01
Date Acceptance
2019-11-01
Citation
IEEE Journal of Biomedical and Health Informatics, 2019, 23 (6), pp.2245-2246
ISSN
2168-2194
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
2245
End Page
2246
Journal / Book Title
IEEE Journal of Biomedical and Health Informatics
Volume
23
Issue
6
Copyright Statement
© 2019 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.
Sponsor
Engineering & Physical Science Research Council (E
British Council (UK)
British Council (UK)
Identifier
https://ieeexplore.ieee.org/document/8894188
Grant Number
540213 SeNTH plus
330760239
2017-RLWK9-11046
Publication Status
Published
Date Publish Online
2019-11-07