Intelligent Systems in Biomedicine

The complexity of biological systems, unlike physical science applications, makes the development of computerised systems for medicine not a straightforward algorithmic solution because of the inherent uncertainty which arises as a natural occurrence in these types of applications. Human minds work from approximate data, extract meaningful information from massive data, and produce crisp solutions. Fuzzy logic provides a suitable basis for the ability to summarise and extract from masses of data impinging upon the human brain those facts that are related to the performance of the task at hand. In practice, a precise model may not exist for biological systems or it may be too difficult to model. In these cases fuzzy logic is considered as an appropriate tool for modelling and control, since our knowledge and experience are directly contained and presented in control strategies without explicit mathematical models. This paper surveys the utilisation of fuzzy logic in medical sciences, with an analysis of its possible future penetration. An application involving fuzzy reasoning and control paradigms in anaesthesia is described in some detail.