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Open Access

Peer-reviewed

Research Article

Applied machine learning to identify differential risk groups underlying externalizing and internalizing problem behaviors trajectories: A case study using a cohort of Asian American children

Samrachana Adhikari ,

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

* E-mail: samrachana.adhikari@nyulangone.org

Affiliation Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America

https://orcid.org/0000-0001-9954-5999

⨯
Shiying You,

Roles Formal analysis, Software, Validation, Writing – review & editing

Affiliation Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
⨯
Alan Chen,

Roles Data curation, Formal analysis, Methodology, Software, Visualization, Writing – review & editing

Affiliation Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
⨯
Sabrina Cheng,

Roles Data curation, Resources, Writing – review & editing

Affiliation Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
⨯
Keng-Yen Huang

Roles Conceptualization, Funding acquisition, Investigation, Resources, Supervision, Writing – review & editing

Affiliation Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
⨯

Applied machine learning to identify differential risk groups underlying externalizing and internalizing problem behaviors trajectories: A case study using a cohort of Asian American children

Samrachana Adhikari,
Shiying You,
Alan Chen,
Sabrina Cheng,
Keng-Yen Huang

x

Published: March 3, 2023
https://doi.org/10.1371/journal.pone.0282235

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Mental health and psychiatry
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Children
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Machine learning algorithms
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Machine learning
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Medical risk factors
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Schools
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Forecasting
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