Rudolf Seising

From vagueness in medical thought to the foundations of fuzzy reasoning in medical diagnosis

OBJECTIVEnThis article delineates a relatively unknown path in the history of medical philosophy and medical diagnosis. It is concerned with the phenomenon of vagueness in the physicians style of thinking and with the use of fuzzy sets, systems, and relations with a view to create a model of such reasoning when physicians make a diagnosis. It represents specific features of medical ways of thinking that were mentioned by the Polish physician and philosopher Ludwik Fleck in 1926. The paper links Lotfi Zadehs work on system theory before the age of fuzzy sets with system-theory concepts in medical philosophy that were introduced by the philosopher Mario Bunge, and with the fuzzy-theoretical analysis of the notions of health, illness, and disease by the Iranian-German physician and philosopher Kazem Sadegh-Zadeh.nnnMATERIALnSome proposals to apply fuzzy sets in medicine were based on a suggestion made by Zadeh: symptoms and diseases are fuzzy in nature and fuzzy sets are feasible to represent these entity classes of medical knowledge. Yet other attempts to use fuzzy sets in medicine were self-contained. The use of this approach contributed to medical decision-making and the development of computer-assisted diagnosis in medicine.nnnCONCLUSIONnWith regard to medical philosophy, decision-making, and diagnosis; the framework of fuzzy sets, systems, and relations is very useful to deal with the absence of sharp boundaries of the sets of symptoms, diagnoses, and phenomena of diseases. The foundations of reasoning and computer assistance in medicine were the result of a rapid accumulation of data from medical research. This explosion of knowledge in medicine gave rise to the speculation that computers could be used for the medical diagnosis. Medicine became, to a certain extent, a quantitative science. In the second half of the 20th century medical knowledge started to be stored in computer systems. To assist physicians in medical decision-making and patient care, medical expert systems using the theory of fuzzy sets and relations (such as the Viennese fuzzy version of the Computer-Assisted Diagnostic System, CADIAG, which was developed at the end of the 1970s) were constructed. The development of fuzzy relations in medicine and their application in computer-assisted diagnosis show that this fuzzy approach is a framework to deal with the fuzzy mode of thinking in medicine.

Review: On the absence of strict boundaries-Vagueness, haziness, and fuzziness in philosophy, science, and medicine

This contribution deals with developments in the history of philosophy, logic, and mathematics during the time before and up to the beginning of fuzzy logic. Even though the term fuzzy was introduced by Lotfi A. Zadeh in 1964/1965, it should be noted that older concepts of vagueness and haziness had previously been discussed in philosophy, logic, mathematics, applied sciences, and medicine. This paper delineates some specific paths through the history of the use of these loose concepts. Vagueness was avidly discussed in the fields of logic and philosophy during the first decades of the 20th century-particularly in Vienna, at Cambridge and in Warsaw and Lvov. An interesting sequel to these developments can be seen in the work of the Polish physician and medical philosopher Ludwik Fleck. Haziness and fuzziness were concepts of interest in mathematics and engineering during the second half of the 1900s. The logico-philosophical history presented here covers the work of Bertrand Russell, Max Black, and others. The mathematical-technical history deals with the theories founded by Karl Menger and Lotfi Zadeh. Mengers concepts of probabilistic metrics, hazy sets (ensembles flous) and micro-geometry as well as Zadehs theory of fuzzy sets paved the way for the establishment of soft computing methods using vague concepts that connote the nonexistence of sharp boundaries.

Between Empiricism and Rationalism: A Layer of Perception Modeling Fuzzy Sets as Intermediary in Philosophy of Science

In philosophy of science we find two epistemological traditions: rationalism and empiricism. Rationalists believe that the criterion of knowledge is not sensory but intellectual and deductive whereas from the empiricist point of view the source of our knowledge is sense experience. Bridging this gap between these theories of knowledge has been a problem in philosophical approaches, both past and present. This philosophical paper focuses on using fuzzy sets and systems (FSS), computing with words (CW), and the computational theory of perceptions (CTP) as methodologies to help bridge the gap between systems and phenomena in the real world and scientific theories. It presents a proposal in which fuzzy methods are used to extend the so-called structuralist view of scientific theories in order to rep resent the relation of empiricism and theoretical structures in science.

Pioneers of Vagueness, Haziness, and Fuzziness in the 20thCentury1

This contribution deals with developments in the history of philosophy, logic, and mathematics during the time before and up to the beginning of fuzzy logic. Even though the term “fuzzy” was introduced by Lotfi A. Zadeh in 1964/65, it should be noted that older concepts of “vagueness” and “haziness” had previously been discussed in philosophy, logic, mathematics, applied sciences, and medicine. This paper delineates some specific paths through the history of the use of these “loose concepts”. Vagueness was avidly discussed in the fields of logic and philosophy during the first decades of the 20

40 years ago: "fuzzy sets" is going to be published

th

Can Fuzzy Sets Be Useful in the (Re) Interpretation of Uncertainty in Quantum Mechanics

century – particularly in Vienna, at Cambridge and in Warsaw and Lvov. An interesting sequel to these developments can be seen in the work of the Polish physician and medical philosopher Ludwik Fleck.

The Gap Between Scientific Theory and Application: Black and Zadeh - Vagueness and Fuzzy Sets

Original research work on the rise of the theory of fuzzy sets is discussed. It is a reconstruction of Lotfi Zadehs contributions to system theory which was a very new scientific discipline at that time. Some details on the historical background of the development of the theory of fuzzy sets are given. A result of this contribution in the history of sciences is: The genesis of the concepts of fuzzy sets and fuzzy systems is a part of system theory in the 1960s.

Is soft computing in technology and medicine human-friendly?

New scientific theories have been and will always be required for the progress of science. Two examples of new theories that were advanced in the 20th century are quantum mechanics and fuzzy set theory. Both deal with the concept of uncertainty and both use mathematical tools that are essentially different from those used in classical probability theory. In both, the introduction of new concepts (theoretical terms) was necessary because phenomena and processes observed in the real world could not be explained with existing mathematical concepts. This paper examines the possibilities of (re)interpreting uncertainty in quantum mechanics with the aid of fuzzy sets and systems

From vague or loose concepts to hazy and fuzzy sets: human understanding versus exact science

In this paper we examine important research pertaining to vagueness and fuzziness carried out by 20th century thinkers, especially Max Black and Lotfi A. Zadeh. We discuss discrepancies between scientific theory and the real world. In the process, we consider the application of fuzzy set theory in science as well as in linguistics, and describe the role of natural language as the best representation system human beings have to express their often imprecise and complex thoughts, feelings, and observations. We note similarities in the approaches followed by Black, Zadeh, and their colleagues and show that their analysis of vagueness and fuzziness respectively were attempts to bridge the gap between theory and reality. Finally, we look at recent efforts to use more sophisticated type-2 fuzzy sets to deal with uncertainties

Homer Richards Warner, 1922–2012

In this paper, which is both historical and philosophical, we regard soft computing (synonymous with computational intelligence) to be an approach in artificial intelligence research. Soft computing and fuzzy sets, its core, were founded by Lotfi A. Zadeh. We show his contributions to the establishment of this field of artificial intelligence since 1950 and we propose that it provides proper methods for the development of human-friendly technology and medicine in the 21st century.