Session

DescriptionHPC-powered AI applications are increasingly accurate and robust, but challenges remain when translating these capabilities into real-world prevention and treatment routines. Central to this issue is the notion of trust, which is essential to all stakeholders in the health care complex: patients, providers, management, and governance. Trustworthy AI systems use transparent reasoning processes, are explainable, accountable, robust, fair, honest, privacy-preserving, and amenable to human goals. In the context of health, all of these aspects are potential blockers to future adoption. In this minisymposium, we will bring in experts from AI model development, health systems analysis, and the clinical translation of AI-integrated cancer treatments.