Fuzzy diagnosis

Starting from the pioneering publication of Lotfi Zadeh in 1965 [55], fuzzy sets have been applied to many fields in which uncertainty plays a key role. Medicine, often on the borderline between science and art, is an excellent exponent: vagueness, linguistic uncertainty, hesitation, measurement imprecision, natural diversity, subjectivity—all these are prominently present in medical diagnosis. While statistical uncertainty can be handled in a rigorous way, the treatment of non-statistical uncertainty is still a challenge [22]. For example, the non-statistical uncertainty in ‘high’, attributed to the blood pressure of a patient, is at least threefold: “ The patient. For a normally hypotonic patient ‘high’ blood pressure is something quite different from what it is for a normally hypertonic patient. “ The expert. Different experts have different opinions about what values of the variable blood pressure should be called ‘high’. “ The diagnostic problem. Definitions depend on the medical context. During anaesthesia for example, what is labelled ‘high’ blood pressure may well be ‘normal’ in another context.