Machine Learning (ML) for Anomaly Detection
A major media topic in 2018 was the fraud cases in the German care system. On 16.10.2018 wrote Spiegel, that according to expert estimates, "around two billion euros will be lost annually through fraud in outpatient care alone". The interest in counteracting this is high. Finding fraud cases well in data therefore appears to be a worthwhile goal.
We have set ourselves the task of analysing, optimising and implementing ML algorithms for detecting conspicuousness. In particular, we focus on assistance systems for users. This branch of research is called Anomaly Detection.