Precision Psychiatry Working Group

We integrate multimodal datasets and AI-driven methods to improve diagnosis and outcome prediction in mental disorders. Our focus has been on risk assessment for bipolar disorder, using machine learning on large-scale, multi-site datasets such as the Early-BipoLife study. We also apply large language models to medical records and speech data to predict psychiatric symptoms, emergencies, and to improve early detection of mental disorders such as psychosis or bipolar disorder.

As part of the The International Research Training Group IRTG 2773, our early career scientists attend research stays at the Institute of Psychiatry, Psychology and Neuroscience King's College London to collaborate on joint projects. We work closely with the EKFZ for Digital Health and are involved in the DFG funded CRC393 consortium. Our research aims to advance precision psychiatry by utilising cutting-edge AI technologies.

Members:

Pavol Mikolas , PhD (lead), Publications

Fabian Huth, MSc

Falk Gerrik Verhees, Publications

Guillermo Calvi

Vincent Meyer

Paula Gutekunst