Harvard model predicts suicide attempts with 75% accuracy up to a week in advance

The research addresses suicide attempts, a leading cause of preventable death, with potential to save lives through early intervention.

At Harvard, researchers have built a machine learning model that can forecast suicide attempts up to one week in advance with 75% accuracy — a development that, if it endures scrutiny, would mark a quiet but profound shift in how medicine approaches one of its oldest failures: arriving too late. Like meteorologists who learned to read the atmosphere before the storm, these scientists are asking whether the patterns hidden in patient data might give clinicians something rare and precious — time. The work is not yet a clinical tool, but it opens a door that has long been sealed, suggesting that

Harvard model predicts suicide attempts with 75% accuracy up to a week in advance

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