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18
On Examination of Medical Data
with Approximate Reasoning
Vesa A. Niskanen
18.1
Introduction
Modern medicine applies both quantitative and qualitative methods because its
scope covers both natural and human sciences. In the former case numerical data,
computer modeling and mathematical and statistical methods are essential, whereas
the latter mainly operates with non-numerical materials, manual work and with such
reasoning as interpretation.
We will consider how computational intelligence (which is sometimes also re-
ferred to as soft computing) may be applied to quantitative medical research, and
this study is inspired by Lotfi Zadeh's recent work and the topic of Kazem Sadegh-
Zadeh [17]. Computational intelligence comprises such methods as fuzzy systems,
neural nets, probabilistic reasoning and evolutionary computing, and it provides us
with usable tools for examining empirical data and medical phenomena in a more
thorough and convenient manner. Today we have mainly applied computational
intelligence to quantitative studies, but it also seems usable in qualitative research.
In particular, we consider below the role of computational intelligence in statis-
tical research in the light of medical data. Hence, we examine how we may replace
or enhance certain statistical analyses with our novel methods in order to achieve
better results. Our methods stem from Lotfi Zadeh's novel fuzzy extended logic,
fuzzy cluster analysis and fuzzy modeling in general, and then we apply them to re-
gression analysis. We also provide some ideas for applying our models to analysis
of covariance and novel clustering techniques.
Chapter 18.2 presents some basic principles of linguistic reasoning and fuzzy
extended logic. Chapter 18.3 considers regression modeling from both the tra-
ditional and computational intelligence standpoint. Chapter 18.4 deals with dis-
criminant analysis. Chapter 18.5 provides some ideas on applying computational
intelligence to analysis of covariance and cluster analysis. Chapter 18.6 concludes
our examination.
 
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