Machine learning-based prediction of suicidality in adolescents during the COVID-19 pandemic (2020–2021): Derivation and validation in two independent nationwide cohorts

Rosie Kwon; Hayeon Lee; Min Seo Kim; Jinseok Lee; Dong Keon Yon

doi:10.1016/j.ajp.2023.103704

Machine learning-based prediction of suicidality in adolescents during the COVID-19 pandemic (2020–2021): Derivation and validation in two independent nationwide cohorts

Rosie Kwon, Hayeon Lee, Min Seo Kim, Jinseok Lee, Dong Keon Yon

Research output: Contribution to journal › Letter › peer-review

13 Citations (Scopus)

Original language	English
Article number	103704
Journal	Asian Journal of Psychiatry
Volume	88
DOIs	https://doi.org/10.1016/j.ajp.2023.103704
Publication status	Published - Oct 2023

Keywords

Adolescents
COVID-19
Korea
Machine learning
Pandemic
Suicidality

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.ajp.2023.103704

Cite this

@article{dbc4f569ad194698991f86bc76acb640,

title = "Machine learning-based prediction of suicidality in adolescents during the COVID-19 pandemic (2020–2021): Derivation and validation in two independent nationwide cohorts",

keywords = "Adolescents, COVID-19, Korea, Machine learning, Pandemic, Suicidality",

author = "Rosie Kwon and Hayeon Lee and Kim, {Min Seo} and Jinseok Lee and Yon, {Dong Keon}",

year = "2023",

month = oct,

doi = "10.1016/j.ajp.2023.103704",

language = "English",

volume = "88",

journal = "Asian Journal of Psychiatry",

issn = "1876-2018",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Machine learning-based prediction of suicidality in adolescents during the COVID-19 pandemic (2020–2021)

T2 - Derivation and validation in two independent nationwide cohorts

AU - Kwon, Rosie

AU - Lee, Hayeon

AU - Kim, Min Seo

AU - Lee, Jinseok

AU - Yon, Dong Keon

PY - 2023/10

Y1 - 2023/10

KW - Adolescents

KW - COVID-19

KW - Korea

KW - Machine learning

KW - Pandemic

KW - Suicidality

UR - http://www.scopus.com/inward/record.url?scp=85166622529&partnerID=8YFLogxK

U2 - 10.1016/j.ajp.2023.103704

DO - 10.1016/j.ajp.2023.103704

M3 - Letter

C2 - 37541104

AN - SCOPUS:85166622529

SN - 1876-2018

VL - 88

JO - Asian Journal of Psychiatry

JF - Asian Journal of Psychiatry

M1 - 103704

ER -

Machine learning-based prediction of suicidality in adolescents during the COVID-19 pandemic (2020–2021): Derivation and validation in two independent nationwide cohorts

Keywords

UN SDGs

Access to Document

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Cite this