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Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches

Huw Prosser Evans, Athanasios Anastasiou Orcid Logo, Adrian Edwards, Peter Hibbert, Meredith Makeham, Saturnino Luz, Aziz Sheikh, Liam Donaldson, Andrew Carson-Stevens

Health Informatics Journal, Start page: 146045821983310

Swansea University Author: Athanasios Anastasiou Orcid Logo

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Published in: Health Informatics Journal
ISSN: 1460-4582 1741-2811
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa49691
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first_indexed 2019-03-21T13:59:27Z
last_indexed 2019-06-12T14:55:55Z
id cronfa49691
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spelling 2019-06-12T10:00:00.3696799 v2 49691 2019-03-21 Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches 77b6898ebedef0c5f84b39b0217c18ce 0000-0002-3504-9969 Athanasios Anastasiou Athanasios Anastasiou true false 2019-03-21 PMSC Journal Article Health Informatics Journal 146045821983310 1460-4582 1741-2811 31 12 2019 2019-12-31 10.1177/1460458219833102 COLLEGE NANME Medicine COLLEGE CODE PMSC Swansea University 2019-06-12T10:00:00.3696799 2019-03-21T11:41:21.6893378 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Huw Prosser Evans 1 Athanasios Anastasiou 0000-0002-3504-9969 2 Adrian Edwards 3 Peter Hibbert 4 Meredith Makeham 5 Saturnino Luz 6 Aziz Sheikh 7 Liam Donaldson 8 Andrew Carson-Stevens 9
title Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
spellingShingle Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
Athanasios Anastasiou
title_short Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
title_full Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
title_fullStr Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
title_full_unstemmed Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
title_sort Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches
author_id_str_mv 77b6898ebedef0c5f84b39b0217c18ce
author_id_fullname_str_mv 77b6898ebedef0c5f84b39b0217c18ce_***_Athanasios Anastasiou
author Athanasios Anastasiou
author2 Huw Prosser Evans
Athanasios Anastasiou
Adrian Edwards
Peter Hibbert
Meredith Makeham
Saturnino Luz
Aziz Sheikh
Liam Donaldson
Andrew Carson-Stevens
format Journal article
container_title Health Informatics Journal
container_start_page 146045821983310
publishDate 2019
institution Swansea University
issn 1460-4582
1741-2811
doi_str_mv 10.1177/1460458219833102
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 0
active_str 0
published_date 2019-12-31T04:00:52Z
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score 11.013776