Information Technology Reference
In-Depth Information
Due to its extended vagueness, medicine provides fertile ground for FLw and
its subtheories from fuzzy set theory to possibilistic logic to fuzzy pattern recog-
nition to fuzzy sensors and automata and additional yet-to-emerge methods and
techniques. All of these conceptual frameworks and technologies will serve as
a welcome medical intelligence enhancing tool and method. Research and prac-
tice of the following type have already advanced worldwide and may exponentially
increase in the years ahead:
•
Studies in the fuzzy foundations of medicine, e.g. concepts of fuzzy health,
illness, disease, recovery, therapy, treatment efficacy, etc.;
•
Applied fuzzy logic in all fields of medical research and practice, e.g.
fuzzy
anatomy, fuzzy physiology, fuzzy biochemistry, fuzzy pathology, etc.
•
Fuzzy systems theory in medicine, e.g. theories of organism, consciousness,
psyche, psychosomatic systems, infection systems, immune systems, etc.;
•
Fuzzy signal processing, e.g. EEG, ECG, EMG, ERG;
•
Fuzzy monitoring, e.g. in intensive care units;
•
Fuzzy adaptive control, e.g. in anesthesia, intensive care units, therapeutic de-
vices;
•
Fuzzy image processing, e.g. in radiology, clinical anatomy, and clinical spe-
cialties;
•
Fuzzy clustering, e.g. in nosology and epidemiology;
•
Fuzzy pattern recognition, e.g. in genetics and genomics;
•
Fuzzy organ support and prosthesis, e.g. in rehabilitation medicine;
•
Fuzzy databases and data engineering, e.g. in hospitals and laboratories;
•
Fuzzy analysis and interpretation of laboratory data, e.g.
in pathology and
clinical-chemistry laboratories;
•
Fuzzy sensors in all medical domains;
•
Fuzzy medical linguistics and terminology, yet to be developed;
•
Fuzzy medical knowledge discovery, yet to be developed;
•
Methodology of fuzzy concept and theory formation in medicine, yet to be de-
veloped;
•
Fuzzy anamnestics, yet to be developed by utilizing branching questionnaires;
•
Fuzzy medical knowledge engineering in every medical domain;
•
Fuzzy clinical reasoning, e.g. in diagnostic-therapeutic decision-making.
An increasingly important role in this evolution will certainly play the latter two
subdomains by utilizing the core fuzzy logic, i.e. fuzzy set theory plus linguistic
variables plus FLn to contribute to the development of fuzzy artificial intelligence.
References
1. Roberto, C., D'Ottaviano Itala, M.L., Mundici, D.: Algebraic Foundations of Many-
Valued Reasoning. Kluwer Academic Publishers, Dordrecht (2000)
2. Gottwald, S.: Mathematical fuzzy logic as a tool for the treatment of vague information.
Information Sciences 172, 41-71 (2005)
