The last few decades have given rise to the idea of personalized or precision medicine for complex disorders or diseases. This development has become feasible through the invention and application of big data and machine learning methods. However, a clear path from the average to the individual patient for most disorders and diseases has yet to be found. In this talk, Thomas Wolfers, discusses principles that may overcome this obstacle. In doing so he makes a case for the importance of normative modeling and shows applications of this approach that move the focus from the average to the individual patient with a complex mental disorder.

About Thomas Wolfers
Thomas Wolfers holds a PhD from the Donders Institute at the Radboud University in Nijmegen, the Netherlands. Currently, he works as a Marie Curie Fellow at NORMENT, a research center on mental disorders at the University of Oslo in Norway. Thomas’ work is focused on utilizing machine learning methods for a better understating of complex disorders and diseases.