Work

Can machine learning identify childhood characteristics that predict future development of bipolar disorder a decade later?

Year: 2022

Type: article

Study design: Observational Study

Source: Journal of Psychiatric Research

DOI: 10.1016/j.jpsychires.2022.09.051

Authors: Mai Uchida, Qasim Bukhari, Maura DiSalvo, Allison Green, Giulia Serra, Chloe Hutt Vater, Satrajit S. Ghosh, Stephen V. Faraone, John D.E. Gabrieli, Joseph Biederman

Institutions: Harvard University, Massachusetts General Hospital, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Indiana University Bloomington, Indiana University, Bambino Gesù Children's Hospital, SUNY Upstate Medical University

Language: English

Topic: Bipolar Disorder and Treatment

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: European Commission, National Institute of Mental Health, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: The Prelude to Psychosis: Brain network analysis in emerging schizophrenia, Neural and Clinical Biomarkers of Risk for ADHD: A Focus on Preschoolers, G434337789, Discoveries in ADHD genomics: Help or hype in clinical settings?, G700313892, Training Program in Integrative Developmental Process, SLE Treatment with N-acetylcysteine

OpenAlex ID: W4306155093

FWCI: 2.118

Cites: 45

Cited by: 16

Related to: 10