7 - Computational intelligence using ontology—A case study on the knowledge representation in a clinical decision support system

Abstract

Computational intelligence has been traditionally associated with neural networks, fuzzy systems, and genetic algorithms. Over the years there have been many developments in computational intelligence. At present, many other fields are part of the study and research in computational intelligence. With advances in cognitive sciences, more techniques of information processing by machines that show characteristics closely associated with human intelligence are being found. Some of these techniques have been studied for a long time, but in recent years there has been some maturity in the understanding and use of these techniques. One such technique is the use of semantics in computational intelligence. There has been a long-drawn-out philosophical debate between lingualism, which claims that there is no human thought without language, and “language of thought” theories, which believe that natural language is inessential to private thought. In an attempt to create intelligent machines, the use of semantics for knowledge representation and knowledge-based creation in a system follows the philosophy of lingualism. Different knowledge representations are used in a knowledge-based clinical decision support system. This chapter makes a study of various knowledge representations. The different theories behind the techniques used in the knowledge representations are discussed. The philosophy of lingualism and the use of semantics in computational intelligence are explained, while a study on semantic knowledge representation in clinical decision support systems is made. The conclusion is the explanation as to how ontological engineering can be used to create computational intelligence.