“Will the machines save us? Only if we help them.”
As physicians, we have a duty to serve our community members, our friends and family, and the future. But what if our community is global, our friends and family are more than just those we know personally, and our future is one in which technology enhances how we serve each other.
I believe in this vision and have begun connecting with physicians, innovators, entrepreneurs, and scientists around the globe with my podcast, “Man & Machine.”

Of the thousands of AI applications that have been announced so far, only a handful are used in routine clinical care and none are cited as standards for use in professional clinical guidelines. Does this mean AI has failed to cross the translational chasm? Not indeed, it is just the approach so far has been exploratory rather than driven by implementation science. In this presentation, I cover the reasons and solutions in my presentation.

The advent of Artificial Intelligence (AI) and Machine Learning (ML) has revolutionized medical care in many ways from operating rooms, drug discovery, specialized care pathways, and to how precision medicine is being delivered to patients. However, the question still remains to if and how this powerful platform can help address many of the prevailing health inequities and help improve access, treatment, and outcomes.

Technologic innovation toward enhancing care for children currently utilizes Artificial Intelligence and Machine Learning (AI/ML) as a core component of design. This session will discuss how AI/ML uses data sets to power algorithms, and how this technology can improve access to care while addressing unconscious bias in both diagnosis and treatment. Examples of current technology powered by AI/ML as well as the advocacy with regard to overall health equity will be highlighted.

The need for artificial intelligence continues to grow, but in areas that oftentimes fall outside the roadmap or strategy of healthcare executives or into an area of limited experience and expertise such as artificial intelligence. Large technology vendors and early stage startups have all struggled to introduce and rapidly iterate new solutions to meet the needs of healthcare providers. This discussion will explore the key challenges facing companies trying to expand the use of A.I.