Causality-based transparency and accuracy in system modeling with human-machine collaboration

The main achievement in future analysis is to acquire causality, transparency and accuracy utilizing human-machine collaboration. We propose a process of close interaction between humans and machines for system modeling, which is backed up by a method to combine human expert knowledge with the performance of information criteria. This approach not only promises the best accuracy but also interdisciplinary transparency. The generic technology is then directed to the estimation of visceral fat area based on bioelectrical impedance analysis and on energy consumption management.