ABSTRACT
This conclusion presents some closing thoughts on the concepts discussed in the third part of this book. The third part of the book explains LCR is the empirical-logical construction, the net of paths along which carefully selected data are processed in accordance with predefined criteria based on scientific research. Analytics is essential to emphasize that LCR is not a machine-learning technology that when processed in some original way will yield new knowledge as output. On the contrary, it is an approach developed from conceptual modelling and model-dependent research, where the primary elaborated model is used to generate data that are then compared with actually measured data. For classical operative research and analytics such an approach may seem strange because it is more logical than mathematized. But in keeping with the great mathematician Israel Gelfand and his whole mathematical school of disciples and followers this is 'the only way' to generalize essential data about highly diverse human activity and body functioning.
