Machine Learning addresses Mental Health Teen suicide
APPLIED ARTIFICIAL INTELIGENCE & MACHINE LEARNING TO UNDERSTAND AND ADDRESS TEEN SUICIDE IN USA
Mental health is an increasing and significant health challenge for teens in the USA.
Teen Suicide is the #2, number 2, leading cause of death among teens in the USA.
Teen suicide has increased 56% over the past decade when measuring 2017 vs. 2007. The rate is 6 to 22 lives per 100,000 lives for girls and boys.
With COVID and decreased rates of mental health care access, recent research has shown the rate of teen mental health continues to decline.
The unsaid is a scary factor when a recent study has shown ~12% of teens have thought about suicide.
HOW CAN MACHINE LEARNING & ARTIFICIAL INTELLIGENCE HELP TEENS?
Machine Learning and Artificial Intelligence has and can be applied to robust real world data sets to understand the rates and patient journey within in the healthcare data.
The data and hypothesis support there continues to be significant continued social pressures, continued social stigmas surrounding mental health, declining rates of mental health resources and access and mixed ranges of social and school programs to support teens.
Machine Learning and Artificial Intelligence has and can identify the key features contributing to teen suicide, learn where the gaps are and create risks or heat maps for areas at risk and/or under served.
Given teen suicide is increasing an integrated program led by teens, education, healthcare, government and manufacturers is the only way to align all resources to decrease the terrifying trend. Teen suicide increasing 56%, 12% thinking about it, a cost of $1.4/patient and the loss of life 6-22:100K is unfathomable.
(Illustrative; presented at Global Big Data Artificial Intelligence Conference May 2021)