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Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data

Abstract:
Background Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for prediction of suicidal behavior.
Methods and findings The study sample consisted of 541,300 inpatient and outpatient visits by 126,205 Sweden-born patients (54% female and 46% male) aged 18 to 39 (mean age at the vis... Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0002-4602-4388
More by this author
Role:
Author
ORCID:
0000-0002-2104-0963
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Name:
Wellcome Trust
Grant:
202836/Z/16/Z
Publisher:
Public Library of Science
Journal:
PLoS Medicine More from this journal
Volume:
17
Issue:
11
Article number:
e1003416
Publication date:
2020-11-06
Acceptance date:
2020-10-08
DOI:
EISSN:
1549-1676
ISSN:
1549-1277
Pmid:
33156863
Language:
English
Keywords:
Pubs id:
1143697
Local pid:
pubs:1143697
Deposit date:
2021-01-19

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