Study: Machine Learning Algorithms Correctly Classify 93% of Suicidal Patients

A New Way To Listen New research published in the journal Suicide and Life-Threatening Behavior shows how machine learning can help identify suicidal behavior using a person’s spoken or written words. The technology was able to pinpoint which participants in the study were suicidal, mentally ill but not suicidal, or neither in the vast majority of cases. John Pestian and a team of researchers studied 379 patients from emergency departments and inpatient and outpatient centers at three locations between Oct. 2013 and March 2015. The patients, who were classified as suicidal, mentally ill but not suicidal, or neither (serving as the control group), answered standardized behavioral rating tests and took part in a semi-structured interview in which they were asked five open-ended questions such as “Do you have hope?” and “Are…


Link to Full Article: Study: Machine Learning Algorithms Correctly Classify 93% of Suicidal Patients

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