Necessary and sufficient causal ground and effect is measured by fuzzy cardinality and may represent natural edge strength connections in a clinical fuzzy cognitive map

Background: Current clinical trials in medicine use probability-based statistics. Statistics separates the patient's physiologic elements from his body and claims causal correlation. Methods: In this study we derive measures of necessary and sufficient causal ground, formal causal ground and clinical causal effect from the fuzzy subsethood theorem as defined by Kosko. We represent patients as sets as points in a unit hypercube before and after treatment with antiplatelet agents. Results: The measures of formal causal ground and clinical causal effect are in units of cardinality. Using data from 16 patients taking antiplatelet therapy, we derived formal causal ground and clinical causal effect which in an imaginary clinical FCM represent causal edge strengths for nodes of antiplatelet medication. Conclusion: Our causal measures are represented as changes in cardinality in a unit hypercube and can be used instead of probability based statistics to judge the causal relation of medical therapies or conditions.