%0 Journal Article
%T Using natural language processing to classify suicide notes
%J AMIA annual symposium proceedings
%D 2008
%A Pestian, John P.
%A Matykiewicz, Pawel
%A Grupp-Phelan, Jacqueline
%A Arszman Lavanier Ma, S
%A Combs, Jennifer
%A Kowatch, Robert
%V 
%N 
%P 1091-1091
%X 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.<p /> <p>Language: en</p>
%G en
%I American Medical Informatics Association
%@ 1559-4076
%U http://dx.doi.org/