This Springer essential explains the theoretical foundations for knowledge-based interpretation of medical laboratory data. Self-organization of biological structure, non-linear dynamics of complex systems and immunological network theories make it possible to describe pathomechanisms and diagnostics, especially of chronic diseases, as an expression of a phenotypic biology and to develop concepts for causal therapies. The book shows how CSF diagnostics with a diagnostic report integrating all laboratory data can identify disease-typical patterns for the differential diagnosis of bacterial, viral, parasitic, oncological, chronic inflammatory, autoimmunological and psychiatric diseases. A CSF app is provided as a tutorial program. The author Prof. Dr. Hansotto Reiber, University of Göttingen, is retired Professor of Neurochemistry. His current work describes biophysical principles in biology and medicine with a focus on complexity sciences. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.