title: Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient.
abstract: The current scientific model for clinical decision-making is founded on binary or Aristotelian logic, classical set theory and probability-based statistics. Evidence-based medicine has been established as the basis for clinical recommendations. There is a problem with this scientific model when the physician must diagnose and treat the individual patient. The problem is a paradox, which is that the scientific model of evidence-based medicine is based upon a hypothesis aimed at the group and therefore, any conclusions cannot be extrapolated but to a degree to the individual patient. This extrapolation is dependent upon the expertise of the physician. A fuzzy logic multivalued-based scientific model allows this expertise to be numerically represented and solves the clinical paradox of evidence-based medicine.
authors.affiliation: Department of Neurology, University of Illinois College of Medicine in Chicago, 912 South Wood Street, Room 855 N, Chicago, IL 60612, USA. helgason@uic.edu
authors.forename: Cathy M
authors.initials: CM
authors.lastname: Helgason
authors.forename: Thomas H
authors.initials: TH
authors.lastname: Jobe
mesh_terms: D019317:Evidence-Based Medicine / Q000639:trends; D017143:Fuzzy Logic; D006801:Humans; D008954:Models, Biological; D020521:Stroke / Q000175:diagnosis* / Q000628:therapy*