A machine learning algorithm that predicts suicide attempt recently underwent a prospective trial at the institution where it was developed, Vanderbilt University Medical Center.

Retrieval of clearer, more complete information from the EHR could go a long way toward improving predictive models of who will next be at risk of suicide, thereby improving care for patients with suicidal thoughts and behaviors.

Investigators will use computational methods to shed light on suicidal ideation and its relationship to attempted suicide, predict suicidal ideation and suicide attempt using routine electronic health records (EHRs) and explore the genetic underpinnings of both.

Using data from the UK Biobank and Vanderbilt’s BioVU, a new study in the journal Molecular Psychiatry finds that approximately 4 percent of suicide attempt risk is captured by genotype data.

Fibromyalgia patients who regularly visit their physicians are much less likely to attempt suicide than those who do not, according to a new Vanderbilt University Medical Center study published in Arthritis Care & Research.

The number of school-age children and adolescents hospitalized for suicidal thoughts or attempts has more than doubled since 2008, according to a new Vanderbilt-led study published in Pediatrics.

According to the Centers for Disease Control and Prevention (CDC), in 2013 there were 41,149 suicides in the U.S., making it the 10th leading cause of death that year. Among high school students in 2013, the CDC estimates that over the previous 12 months 2.7 percent had sometime made a suicide attempt resulting in injury, poisoning or overdose that required medical attention.