September 16 @ 4:00 – 5:00 pm
Speakers: Ketan K. Mane, PhD and Chris Bizon, PhD
Current evidence-based approaches take substantial time to make informed decisions. Here we discuss a novel visual analytics approach that helps to quickly determine viable treatment options at the point of care based on comparative models. In this approach, visual cues reduce information overload and help guide the data interpretation process. Inbuilt visual interactions can be used to retrieve details for additional insights. We also discuss our investigations into differing approaches to construct the comparison population sets that treatment options are based upon.
RENCI Project Members: Ketan K. Mane, Chris Bizon, and Charles Schmitt
Ketan Mane is a Senior Research Informatics Developer in Biosciences and Health Team at Renaissance Computing Institute (RENCI). His work is focused on applying visual analytics approach to practice of evidence-based medicine. His research interest include: information visualization, evidence-based medicine, visual analytics, public health using web 2.0 technologies, and knowledge domain visualization. Prior to this, he worked as a Postdoctoral Research Fellow at Los Alamos National Lab (LANL) on emergency information synthesis and awareness related projects. Ketan has a background in biomedical engineering, and holds a Ph.D. in Information Science from Indiana University, Bloomington, 2006.
Chris Bizon original training is as a physicist. He holds a Ph.D. in Physics from the University of Texas at Austin where he studied the numerical modeling of nonlinear phenomena. Following a postdoc at Colorado Research Associates simulating atmospheric turbulence, he worked as a software developer at webslingerZ, Inc in Chapel Hill. He later joined the Cheminformatics group at GlaxoSmithKline in RTP, where he worked on statistical modeling in drug discovery. He is currently a Senior Research Scientist at the Renaissance Computing Institute.