Examples of current research work in the group "AI & Data Science"

Alzheimer early

Retrospectively validated AI model allows early detection of Alzheimer's 6 years in advance

Molecular subtypes


Innovative AI approach allows identification of prognostically relevant molecular cancer subtypes based on multi-omics data


Drug target


AI approaches allow efficient prioritization of potential drug targets

Synthetic data


Innovative AI approach allows the generation of realistic synthetic patient trajectories

Mechanisms based patient stratification

AI allows for stratification of Alzheimer and Parkinson patients via molecular disease mechanisms - a step towards Precision medicine in neurology


Progression Subtypes


New AI approach allows for clustering of multivariate longitudinal patient trajectories and detection of progression subtypes in Alzheimer's and Parkinson's Disease



Explainable AI


An explainable AI approach allows for predicting comorbidity risks of individual epileptic patients using large scale clinical routine data. Within the Fraunhofer Center for Machine Learning we developed a demonstrator to showcase this approach.

Predicting drug response


Towards realizing the vision of precision medicine: AI allows for predicting response to anti-epileptic drug


New Drug Candidates for COVID-19

AI Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases.