This team is led by principal investigators Dr. Andrew Boyd, Dr. Catherine K. Craven, and Dr. Karen Dunn Lopez. Over a dozen other researchers and practitioners, from four different universities, are also engaged in the project. Over the course of the grant, this team will collaborate to:

​

• Gather, secure, and extract multidisciplinary data

• Train AI models on new clinical concepts and terminology

• Identify if there are any gaps in clinical terminology that will prevent effective training of AI systems, and propose how to address them

• Create and evaluate AI generated all-team health care summaries

• Host hackathons to test developed solutions and identify new, additional solutions

• Disseminate the developed datasets, tools, and insights to benefit patient care and health research

 

The initial focus of this research will be to integrate data sets from doctors, nurses, physical therapists, occupational therapists, and speech therapists, as these professions are the ones most commonly needed in complex health cases. The data will focus on patients who experience one of two common complex care situations: NICUs and falls that lead to serious injury. By doing this foundational work, the team will pave the way for later research into additional disciplines and health care scenarios.