Using a person's spoken or written words, new computer tools can identify with great accuracy whether that person is suicidal, mentally ill but not suicidal, or neither. Machine learning is up to 93 percent accurate in correctly classifying a suicidal person and 85 percent accurate in identifying a person who is suicidal, has a mental illness but is not suicidal, or neither. These results provide strong evidence for using advanced technology as a decision-support tool to help clinicians and caregivers identify and prevent suicidal behavior, says John Pestian, PhD, professor in the divisions of Biomedical Informatics and Psychiatry at Cincinnati Children's Hospital Medical Center and the study's lead author.
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