Applied AI – Elevate Ideas to Reality

The operationalization of AI solutions in healthcare faces formidable challenges, from ensuring data quality and seamless integration to achieving scalability and maintaining model performance. Integrating AI with existing Health Information Technology (HIT) infrastructure is equally complex, often requiring extensive modifications to outdated systems.

Scalability poses another significant hurdle, as AI solutions must efficiently manage ever-growing volumes of patient data and clinical requests without sacrificing performance and budget. Moreover, continuous monitoring and proactive maintenance are crucial to address model drift and guarantee that AI systems remain effective, reliable, and capable of transforming patient care. Please join us as we share and discuss systematic approaches to overcoming these challenges. From proper problem scoping to starting with non-AI solutions, many federal programs have achieved remarkable success in public health research, near real-time diagnostic predictions, and advanced clinical decision support. We will focus on these success stories and explore what it takes to transform an idea into a tangible improvement in the quality and duration of people’s lives.