Fuzzy sets in life sciences

摘要: Abstract Beginning with the first attempts to develop computerized systems in medicine and biology, it was recognized that one of significant obstacles inherent uncertainty which arises as a natural occurrence these types applications. Unlike physical science applications, life sciences are not amenable straightforward algorithmic solutions for number reasons, including lack complete understanding mechanisms biological organisms, inability obtain information regarding state organism, precise ranges normal values physiological parameters, complications caused by interaction several functioning simultaneously. The most complex human, is difficult model. In fact, efforts have been toward developing medical decision-support systems. Because uncertainties, creative approaches were sought both modeling decision making sciences. Initially, statistical pattern recognition tried, followed decade research into knowledge-based Neural network also used beginning late 1960s. This approach met little success but reemerged 1980s, new algorithms faster computers, become primary making. Although early presence uncertainty, usually dealt within ad hoc fashion. Only last fifteen years techniques from fuzzy logic applied extensively However, short time, made inroads problems producing practical support