Machine-Learning Algorithms Can Predict Suicide Risk More Readily Than Clinicians, Study Finds

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    Profile photo of Nnamdi Onwumere
    Nnamdi Onwumere
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    Newsweek, 2/27/2017

    Human clinicians are known not to be very accurate at predicting suicides, so researchers are developing machine-learning algorithms that use multiple factors to identify short-term suicide risk. Data scientists trained the algorithm on data from thousands of clinical records, from both non-fatal suicide cases and random patients. Accuracy was significantly better than studying only one risk factor at a time. Using such a system could aid clinicians in targeting at-risk patients and treating them early.

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