Suicide continues to be a leading cause of death and has been recognized as a significant public health issue. Rapid advances in data science can provide us with useful tools for suicide prevention, and help to dynamically assess suicide risk in quantitative data-driven ways. In this article, the authors highlight the most current international research in digital suicide prevention, including the use of machine learning, smartphone applications, and wearable sensor driven systems. The authors also discuss future opportunities for digital suicide prevention, and propose a novel Sensor-driven Mental State Assessment System.
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