Citation

Mangino AA, Smith KA, Finch WH, Hernández-Finch ME. Meas. Eval. Counsel. Dev. 2022; 55(2): 116-135.

Copyright

(Copyright © 2022, Association for Measurement and Evaluation in Counseling and Development (U.S.), Publisher SAGE Publishing)

DOI

10.1080/07481756.2021.1906156

PMID

unavailable

Abstract

A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.

Language: en

Keywords

Accuracy; Artificial Intelligence; Bayesian Statistics; Classification; Health Behavior; High School Students; Measurement; Models; National Surveys; Networks; Outcome Measures; Prediction; Regression (Statistics); Risk; Suicide