Special Interest Groups
SIG: Data Science in Epilepsy: Effective Data Visualization
Data visualization is nothing new. In the past two decades, the newly coined term of Data Science has emerged to encompass portions of a number of overlapping fields including psychology, mathematics, engineering, computer science, statistics, and of course artificial intelligence/machine learning. Today there is more data than ever, and more advanced ways to process this data into useful information. That sounds like a good thing. The bad thing is that we can visualize this huge influx of data in an infinite set of possible representations, and a whole bunch of them are terrible at communicating important ideas. What Data Science offers is a reasoned approach to this problem, offering a suite of options but also a selection of best practices, rules of thumbs and even specific things NOT to do. This year's SIG will focus exactly on these three problems: how should scientists visualize their own data to themselves and their peers? How should clinicians expect data to be visualized? How should patients expect data to be visualized? If we don't think deeply about these questions, we will do great science and communicate it all very poorly. If we do, the hope is we can be more effective at all three problems. This will be an interactive SIG session.
Coordinators: Daniel M Goldenholz, MD, PhD and Brian Litt, MD
Speakers: Sharon Chiang, MD, PhD, and Ketan Mane, PhD