Navigating the Big Data Maze

The progression of Parkinson’s disease varies greatly from person to person. Scientific advancements allow us to measure a variety of biological markers (e.g. DNA, RNA and protein) from a simple blood sample. Can we combine these measures to give a clearer insight into the progression of the disease in an individual?

Scientific research output is growing faster than we can read it, and some of the most important findings might get lost in the noise. Could machines help us catch up? In this talk, we explore how natural language processing (NLP) is being used to extract meaning from a messy, complicated pile of research articles. From human trial data to animal studies, we’ll see how AI might help bridge gaps in knowledge, but also why teaching machines to "understand" science is far from straightforward.