Citation

Pestian J, Matykiewicz P, Grupp-Phelan J, Arszman Lavanier Ma S, Combs J, Kowatch R. AMIA Annu. Symp. Proc. 2008; 1091.

Affiliation

Univ Cincinnati, Cincinnati Children's Hospital Medical Center.

Copyright

(Copyright © 2008, American Medical Informatics Association)

DOI

unavailable

PMID

19006447

Abstract

We hypothesize that machine-learning algorithms (MLA) could classify completer and ideator suicide notes as well a mental health professionals (MHP). Five MHPs classified 66 notes as either ideator or completer; machine learning algorithms (MLA) were used for the same task. Results: MHPs were accurate 71% of the time; the SMO algorithm was accurate 79% of the time. This is an important first step in developing an evidence based suicide predictor for emergency department use.

Language: en