Causality in digital medicine
File(s)Causality in digital medicine.pdf (468.41 KB)
Published version
Author(s)
Glocker, Ben
Musolesi, Mirco
Richens, Jonathan
Uhler, Caroline
Type
Journal Article
Abstract
Ben Glocker (an expert in machine learning for medical imaging, Imperial College London), Mirco Musolesi (a data science and digital health expert, University College London), Jonathan Richens (an expert in diagnostic machine learning models, Babylon Health) and Caroline Uhler (a computational biology expert, MIT) talked to Nature Communications about their research interests in causality inference and how this can provide a robust framework for digital medicine studies and their implementation, across different fields of application.
Date Issued
2021-09-15
Date Acceptance
2021-09-01
Citation
Nature Communications, 2021, 12 (1), pp.1-6
ISSN
2041-1723
Publisher
Nature Research
Start Page
1
End Page
6
Journal / Book Title
Nature Communications
Volume
12
Issue
1
Copyright Statement
© Springer Nature Limited 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000697264200001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
Publication Status
Published
Article Number
ARTN 5471
Date Publish Online
2021-09-15