How the number of measured dimensions affects fuzzy causal measures of vitamin therapy for hyperhomocysteinemia in stroke patients

As a natural sequel to our investigations in the application of the fuzzy model to clinical stroke diagnosis and treatment, we have developed direct measures of causality sensitive to initial conditions of the individual patient with stroke and are based on the fuzzy measure M of cardinality and the fuzzy subsethood theorem defined Kosko. In this paper we show and measure the effect of a previously un-represented element (dimension) on our causal clinical efficiency measure K sensitive to unique initial and final conditions. We show this by adding the new element to the patient as fuzzy set. Again, our causal measures are based on the same measure of fuzzy cardinality M and the fuzzy subsethood theorem. The definition of causal measures for Formal Causal Ground (FCG), Clinical Causal Effect (CCE) and K can be found. Two separate measures for K are calculated. The clinical efficiency of Foltx when the genetic mutation is included as information in the patient fuzzy set, and when it is not. The effect of the addition of elemental information as variable in the patient's fuzzy set is discussed.