dc.contributor.author | Michie, Susan | |
dc.contributor.author | Thomas, James | |
dc.contributor.author | Johnston, Marie | |
dc.contributor.author | Mac Aonghusa, Pol | |
dc.contributor.author | Shawe-Taylor, John | |
dc.contributor.author | Kelly, Michael P. | |
dc.contributor.author | Deleris, Léa A. | |
dc.contributor.author | Finnerty, Ailbhe N. | |
dc.contributor.author | Marques, Marta M. | |
dc.contributor.author | Norris, Emma | |
dc.contributor.author | O'Mara-Eves, Alison | |
dc.contributor.author | West, Robert | |
dc.date.accessioned | 2017-10-25T10:10:14Z | |
dc.date.available | 2017-10-25T10:10:14Z | |
dc.date.issued | 2017-10-18 | |
dc.identifier.citation | Michie , S , Thomas , J , Johnston , M , Mac Aonghusa , P , Shawe-Taylor , J , Kelly , M P , Deleris , L A , Finnerty , A N , Marques , M M , Norris , E , O'Mara-Eves , A & West , R 2017 , ' The Human Behaviour-Change Project : harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation ' , Implementation Science , vol. 12 , 121 , pp. 1-12 . https://doi.org/10.1186/s13012-017-0641-5 | en |
dc.identifier.issn | 1748-5908 | |
dc.identifier.other | PURE: 110468093 | |
dc.identifier.other | PURE UUID: e63b7767-f078-4c8b-84d8-051ad49156ed | |
dc.identifier.other | Scopus: 85034114839 | |
dc.identifier.uri | http://hdl.handle.net/2164/9499 | |
dc.description | The project is funded by a Wellcome Trust collaborative award [The Human Behaviour-Change Project: Building the science of behaviour change for complex intervention development’, 201,524/Z/16/Z]. During the preparation of the manuscript RW’s salary was funded by Cancer Research UK. | en |
dc.format.extent | 12 | |
dc.language.iso | eng | |
dc.relation.ispartof | Implementation Science | en |
dc.rights | © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. | en |
dc.subject | SDG 3 - Good Health and Well-being | en |
dc.subject | Behaviour change interventions | en |
dc.subject | Implementation | en |
dc.subject | Ontology | en |
dc.subject | Machine learning | en |
dc.subject | Natural language processing | en |
dc.subject | Evidence synthesis | en |
dc.subject | Artificial intelligence | en |
dc.subject | R Medicine (General) | en |
dc.subject | Wellcome Trust | en |
dc.subject | 201,524/Z/16/Z | en |
dc.subject | Cancer Research UK | en |
dc.subject.lcc | R1 | en |
dc.title | The Human Behaviour-Change Project : harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation | en |
dc.type | Journal article | en |
dc.contributor.institution | University of Aberdeen.Other Applied Health Sciences | en |
dc.description.status | Peer reviewed | en |
dc.description.version | Publisher PDF | en |
dc.identifier.doi | https://doi.org/10.1186/s13012-017-0641-5 | |
dc.identifier.vol | 12 | en |