Researchers at Carnegie Mellon did a very small but provocative study with functional MRI brain images of seventeen suicidal ideators and seventeen controls.40 Machine learning algorithms could accurately detect “neurosemantic” signatures associated with suicide attempts. Each individual, while undergoing the MRI, was presented with three sets of ten words (like “death” or “gloom”). Six words and five brain locations determined a differentiating pattern. Machine learning classified the brain image response correctly in fifteen of the seventeen patients in the suicide group and sixteen of the
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