Let us get practical: developing and disseminating AI research and workflows to audiences of researchers and clinicians within BCH using the ChRIS platform
Speaker: Rudolph Pienaar, PhD, Staff Scientist at Boston Children's Hospital
We are often wowed by the *potential* of AI (and frankly other sophisticated computational approaches) to transform research and clinical workflows. New approaches seem to magically hold unbounded promise. Yet, there is often a large gulf between theory and practice, between a shiny new technique and having anyone just use it. The questions of "How do I get this ? How do I get my data from PACS to connect to this? How do I go from DICOM to something that the neural network wants? How do I get results that are useful?" In this talk I will provide some insights into practically developing, using, and disseminating "AI" (and other) workflows in the BCH clinical and research environment.
Dr. Rudolph Pienaar is currently faculty Staff Scientist at Boston Children's Hospital, where he is the Technical Director of the Fetal-Neonatal Neuroimaging and Development Science Center (FNNDSC). The Center aims to play both a research and clinical role in the Boston’s Children's Hospital, and in his capacity at the Center he is engaged in both translational as well as applied research. The goal of the translational research component is to rapidly prototype and deploy complex research-based software within a clinical setting. To this end he heads up a small team developing simple interfaces to creating, managing, and using a wide array of research software, as well as optimizing design and execution of the same. His applied research explores and models the basic processes underpinning human brain development, especially the shape of cortical surfaces and the role this can play in development and disease. Related interests are white matter tractography, specifically the propagation and flow of information through brain networks, as well as investigating relationships between cortical surface markers and internal fiber organization.
