High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning

Abstract We present an ensemble transfer learning method to predict suicide from Veterans Affairs (VA) electronic medical records (EMR). A diverse set of base models was trained to predict a binary outcome constructed from reported suicide, suicide attempt, and overdose diagnoses with varying choice...

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Bibliographic Details
Main Authors: Sayera Dhaubhadel, Kumkum Ganguly, Ruy M. Ribeiro, Judith D. Cohn, James M. Hyman, Nicolas W. Hengartner, Beauty Kolade, Anna Singley, Tanmoy Bhattacharya, Patrick Finley, Drew Levin, Haedi Thelen, Kelly Cho, Lauren Costa, Yuk-Lam Ho, Amy C. Justice, John Pestian, Daniel Santel, Rafael Zamora-Resendiz, Silvia Crivelli, Suzanne Tamang, Susana Martins, Jodie Trafton, David W. Oslin, Jean C. Beckham, Nathan A. Kimbrel, Million Veteran Program Suicide Exemplar Work Group, Benjamin H. McMahon
Format: Article
Language:English
Published: Nature Portfolio 2024-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-51762-9

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