Machine-learning algorithms can dramatically improve ability to predict suicide attempts

Each year in the United States, more than 40,000 people die by suicide, and from 1999 to 2014, the suicide rate increased 24 percent. You might think that after generations of theories and data, we would be close to understanding how to prevent self-harm, or at least predict it. But a new study concludes that the science of suicide prediction is dismal, and the established warning signs about as accurate as tea leaves. There is, however, some hope. New research shows that machine-learning algorithms can dramatically improve our predictive abilities on suicides.