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is related to the absence of crisp boundaries in the membership function. Humans
have the ability to evaluate whether an information belongs gradually to a set, or
not, and the definition of fuzzy membership functions describes this notion. While
the fuzzy set theory is able to deal with information that is simultaneously imprecise
and uncertain, the fuzzy logic allows aggregating different information entailing a
conclusive condition. In the field of medicine, for instance, it is able to deal with
signals and symptoms, laboratorial results, marks, environment etc. for achieving,
only to mention few, risk analysis, assessment, diagnosis, therapeutic conduct.
Fig. 16.1
Human reasoning when dealing with perfect and imperfect information [4]
A historical perspective on the use of the fuzzy set theory and fuzzy logic in
medicine and bio-medical engineering is presented in [30]. Another historical anal-
ysis concerning vagueness as unsharp boundaries sewed with the haziness and fuzzi-
ness concepts in the field of medicine but philosophy, logic, mathematics, applied
sciences, as well, is carried out in [26, 27]. A literature survey on fuzzy sets as a
useful mechanism for medical artificial intelligence is given in [29]. A more spe-
cific survey on the current and future use of fuzziness in medical sciences, encom-
passing areas of (
i
) conservative, (
ii
) invasive, (
iii
) regionally (organ) defined, (
iv
)
neural, medical disciplines as well as (
v
) image and signal processing, (
vi
) labora-
torial analysis, and other (
vii
) basic science disciplines is described in [1]. In this
sense, a review article in medicine and bioinformatics focusing on the geometrical
interpretation of fuzziness in a fuzzy hypercube approach is presented in [31]. A
philosophical background for applying the fuzzy logic to the medical theory and
the understanding of fuzzy health, illness, and disease is discussed in [25]. Such
