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 analysis of social media data is one promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. It can literally save lives.

Data Harmony is Access Innovations’s artificial intelligence (AI) suite of tools that leverage explainable AI for efficient, innovative and precise semantic discovery of new and emerging concepts. By analyzing your content and identifying concepts and terms, Data Harmony can organize and suggest a semantic model to increase the precision and recall of your search. 

Melody K. Smith

Sponsored by Access Innovations, changing search to found.