Applying Machine Learning & AI to Help Prevent Suicide 

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Background 

Suicide is a top 9 leading cause of death in the US.  Veterans are 1.5 times more likely to die by suicide than non-veterans. Suicide and attempts also impact the health of friends, family, co-workers, business, and the community. The financial toll on the economy is also costly. In 2020,  suicide and self-harm cost the nation over $500 billion according to the CDC.   

 

Challenge 

Today, the burden for prevention lies on the individual, already in distress, to self-assess and then seek out solutions, such as enrolling in an assistance program or calling a hotline.  Some organizations perform outreach, but they are limited to making phone calls using a simple list of names on a calendar-based schedule.  There is a better way.   

 

Research-Informed Solution 

ClearForce applies state of the art Machine Learning and AI models trained on the CDC defined categories of data attributes that correlate to high incidents of suicide.   We use evidence-based research informed modeling to accurately identify those who are at the highest risk so they can be prioritized and supported immediately with the goal of preventing tragedy. The output of our model delivers advanced analytics and data visualization products so you can prioritize outreach, prevention support, and reporting.     

 

The Resolve™ Platform and our modeling service can be utilized to continually evaluate a given population across thousands of social, criminal, financial, and health data attributes in real-time with push-based alerts, investigation workflow, and case management.  Our analytics portal provides a secure interface for self and 3rd party reports of suicide risk incidents.