Abstract
"Fuzzy" is defined as "blurred" or "not clear" (Webster's New Twentieth Century Dictionary, 1957). In Japanese, "Fuzzy" is "曖昧" (a-i-ma-i). These Chinese characters originally mean that a substance can not be seen at dawn or in shadows. However, when once the sun shines, it can be clearly noticed. It has a definate core even though it is vague or ambiguous. Natural languages (categorical information) have their definate meanings ("langue" by Saussure), but the meaning must be variously changed in their contexts ("parole" by Saussure). Measured informations as clinical loboratory data are expressed by definate numbers, but they have also different meanings depending on their backgrounds (contexts). When we process the categorical informations in biomedical systems, we usually transform them into the numerical data. The words could not be used directly. We should not use blurred or false data but the correct and most suitable data. Fuzzy inference works most efficiently to discriminate the members and to make a decision. Association of the fuzzy inference in the neural network could afford the most human-like way to process the biomedical data.
