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Retrospectively validated AI model allows early detection of Alzheimer's 6 years in advance
Innovative AI approach allows identification of prognostically relevant molecular cancer subtypes based on multi-omics data
AI approach allows more efficient identification of new drug target structures
Innovative AI approach allows the generation of realistic synthetic patient trajectories
AI allows for stratification of Alzheimer and Parkinson patients via molecular disease mechanisms - a step towards Precision medicine in neurology
New AI approach allows for clustering of multivariate longitudinal patient trajectories and detection of progression subtypes in Alzheimer's and Parkinson's Disease
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.
Towards realizing the vision of precision medicine: AI allows for predicting response to anti-epileptic drug