Identifying causal relationships based on observational data is challenging, because in the absence of interventions (i.e. experiments), causal discovery algorithms have to tackle the problem of observational equivalence. ...

Cyber-physical systems (CPS) are becoming more prevalent for the reliable execution of critical tasks, e.g., in the aerospace and medical fields. The development of such systems is challenging, due to the heterogeneity of ...

The design and operation of modern IT-based systems especially cyber-physical systems (CPS), need modelbased approaches due to their complexity. However, the limited faithfulness of pure analytic models with speculative ...

Oscillometric blood pressure measurement is one of the most commonly used methods to estimate the state of the cardiovascular system. Despite its widespread use, accuracy of the oscillometric method is influenced by several ...

A common question regarding the application of neural networks is whether the predictions of the model are reliable, in other words, what is the degree of uncertainty of our model. Generalizing a neural network into a ...

Model-based technologies improve the efficiency of the design and development of IT systems by making it possible to automate verification, code generation and system analysis based on a formal model. A simple way of ...

Clusters of multimorbidities indicate common molecular and physiological causal mechanisms, which can help to identify promising targets for novel drugs and treatments. We analyzed the comorbidities for COVID-19 death cases ...