Johns Hopkins University researchers have developed a machine learning algorithm that uses predictive analytics to identify adolescents experiencing suicidal thoughts and behavior. Health IT Analytics brought this interesting topic to our attention in their article, “Machine Learning Uses Predictive Analytics For Suicide Prevention.”
Researchers discovered specific risk factors associated with suicidal thought and behavior among adolescents, helping to improve suicide prevention efforts. Few studies have examined these risk factors in combination with each other, especially in a large adolescent population.
Machine learning can now provide new opportunities to study risk factors in adolescents, improving suicide prevention efforts. Machine learning analysis of social media data is one promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors.
Data Harmony is Access Innovations’ artificial intelligence (AI) suite of tools that leverage explainable AI for efficient, innovative and precise semantic discovery of new and emerging concepts. Making the content findable is important to knowledge management, and possibly saving lives.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.
