Among other risks, providers could be held liable for negative patient outcomes resulting from AI that has been inadequately vetted for bias.

While previous research has identified specific risk factors associated with suicidal thoughts and behavior among adolescents, few studies have explored these risk factors in combination with each other.

By understanding how the human brain can be so energy efficient, researchers hope to develop AI that can do more computing with much less consumption of energy.

The U.S. CDC estimates that one in seven children in the United States experienced abuse or neglect in the past year.

According to the World Health Organization, at least 80% of heart disease, stroke, and type 2 diabetes are preventable.

While AI can offer advantages over traditional analytics and clinical decision-making techniques to help improve veteran care, the department aims to ensure any implementation of the technology is both trustworthy and protects veteran information.  

While AI-powered solutions have the potential to revolutionize the diagnosis and treatment of mental illness, providers need to understand the technology better so that the promise can be harnessed without unintended consequences.

The researchers say their approach also enables different researcher groups to compare their models in a consistent and reproducible way.

When it comes to making public policy decisions, new research finds, there really isn’t much of a trade-off between accuracy and fairness when turning to AI for help.