Features of the fuzzy clinical causation measure K

The fuzzy clinical causation measure K which gives a measure of how well the fuzzy unit hypercube of specified variables (dimensions) fits the actual causal matrix of the patient\´s physiology when a patient moves from clinical state A to clinical state B. K is derived from the fuzzy Subsethood Theorem as it applies to clinical causal effect and formal causal ground. Two basic assumptions underlie the formulation. The first is that the physiology of the individual patient is so complex and clinical decisions often life determining that conditions of uncertainty always face the physician. The second is that nature as a whole, the patient\´s physiology in particular, follow the general physical principle of \´least action\´. This formulation elucidates the role of the expert observer as active in the assignment of causality to the physical conditions of the unique individual with the added constraint that the observer is also an individual with a unique history. This approach to causation is contrary to the current practice of "evidence-based medicine" where it is assumed that clinical observers are interchangeable with each other and individual patients are interchangeable with each other.