Predictive Modeling of Suicidal Ideation in Patients with Epilepsy
Matthew D. Nemesure, Nicholas Streltzov, Lindsay M. Schommer, Damien Lekkas, Nicholas C. Jacobson, Krzysztof A. Bujarski
The prevalence of suicide in the United States has seen an increasing trend and is responsible for 1.6% of all mortality nationwide. While suicide has the potential to broadly impact the entire population, it has a substantially increased prevalence in persons with epilepsy (PWE) despite many of these individuals consistently seeing a health care provider. The goal of this work is to predict the development of suicidal ideation in PWE using machine learning methodology such that providers can be better prepared to address suicidality at visits where it is likely to be prominent.