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  • Title: Computer-aided diagnosis and negligence.
    Author: Bainbridge DI.
    Journal: Med Sci Law; 1991 Apr; 31(2):127-36. PubMed ID: 2062195.
    Abstract:
    The phrase 'expert system' has been widely used to describe computer systems which are capable of performing at or near to the level of an expert. Expert systems may be recognized by their construction or by their performance. Structurally, expert systems usually comprise a knowledge-base, an inference engine and an interface with the user as shown in Figure 1. The knowledge-base contains the raw material of the expert system; the rules and facts representing the expertise. An important part of that knowledge-base usually will be heuristic in nature and this is particularly so with respect to expert systems in medicine. A large amount of a specialist's knowledge is informal and experimential in nature and this heuristic knowledge is often what sets the specialist apart from the general practitioner or indeed sets the latter apart from the medical student. The inference engine is a computer program which attempts to resolve the user's enquiries by operating on and interacting with the knowledge-base. Finally, the interface with the user serves two purposes: first, to make the system relatively easy to use and second, and very importantly, to provide an explanation and justification for the results, advice and suggestions obtained from using the system (Winfield, 1982). There will be other parts to an expert system which are used to refine and modify the knowledge-base. The performance of an expert system is of utmost importance and it is the most fundamental test for whether a computer system falls into this classification. d'Agapeyeff (1984) defines expert systems as being: a) programmed to a significant extent, from an explicit representation of empirical human knowledge; b) readable by those who provided the knowledge and, potentially, by similarly knowledgeable users and managers; c) able to provide explanations of their reasoning on demand; d) quickly alterable with (comparatively) low risk of unwanted side effects.' d'Agapeyeff describes the knowledge-base as being empirical, suggesting that it is informal or heuristic knowledge rather than comprising clear and formal rules as written in textbooks. This does not preclude the inclusion of formal knowledge in the expert system but it is clear that heuristic knowledge occupies a key role in the development of expert systems. Much medical knowledge is heuristic in nature; for example, an experienced doctor might use a rule in diagnosis such as: 'If symptoms A and B are observed then C is plausible but certainly not D'. In the field of medicine, expert systems will enable specialist expertise (a rare commodity) to be available to non-specialists such as general practitioners.(ABSTRACT TRUNCATED AT 400 WORDS)
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