This workshop is organized by Peter Klimek, Stefan Thurner and Nils Haug, Medical University of Vienna & CSH Vienna.
Patient health is typically characterized by a combination of clinical conditions and diseases. Often these diseases do not occur independently from each other but in specific temporal patterns. The increasing availability of large-scale observational healthcare data, e.g. electronic health records and claims data, triggered increasing interest into the problem of how to mine such data for temporal patterns and how to use this information to build predictive models for disease trajectories. With this workshop we aim to bring together the world’s leading researchers working on these and related questions in order to discuss open problems and recent advances in an informal atmosphere.
Alexia Giannoula: System level analysis of disease trajectories using clinical, genetic & phenotypic similarities
Nils Haug: History-dependent Modeling of Patient Health Trajectories
Diether Kramer: Machine Learning and Predictive Analytics
Werner Leodolter: Smart Data and Clinical decision support: Strategic aspects of a big healthcare provider
Srebrenka Letina: Using comorbidity networks to understand psychopathology
Markus Strauss: Data-driven identification of disease phenotypes from higher-order correlations