Researchers at Brigham Young, Johns Hopkins, and Harvard universities developed an algorithm which they say is 91% accurate in predicting suicidal thoughts and behavior (STB) among adolescents.
The researchers reviewed data from 179,384 junior high and high school students, plus participants in the 2017 Student Health and Risk Prevention survey; 1.2 billion data points were processed in total. The team applied various algorithms to the data, which yielded a machine learning model that accurately forecast which adolescents later had STB. Females were more likely than males to exhibit STB, while adolescents lacking a father at home also were more likely to think of suicide than those who did not.
From Brigham Young University
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