Artificial intelligence methods and systems for medical consultation

In the maturing field of artificial intelligence (AI), the number of applications increases yearly, medical consultation having been prominent since the early 1970's. Methods of AI were first introduced in the CASNET, MYCIN, INTERNIST, and PIP systems. These and subsequent AI systems are often called knowledge-based because they use highly structured representations of medical knowledge. The interpretation of a patient's clinical problems in terms of such a structure of medical concepts and facts can be carried by methods of symbolic reasoning that have greater expressive power than strictly numerical methods of inference. At the same time there has been a trend towards the introduction of structural constraints in the more classical probabilistic and pattern recognition schemes for medical consultation. The major AI problems that arise in designing a consultation program involve choices of knowledge representations, diagnostic interpretation strategies, and treatment planning strategies. The need to justify decisions and update the knowledge base in the light of new research findings places a premium on the modularity of a representation and the ease with which its reasoning procedures can be explained. In both diagnosis and treatment decisions, the relative advantages and disadvantages of different schemes for quantifying the uncertainty of inferences raises difficult issues of a formal logical nature, as well as many specific practical problems of system design. An important insight that has resulted from the design of several artificial intelligence systems is that robustness of performance in the presence of many uncertainty relationships can be achieved by eliciting from the expert a segmentation of knowledge that will also provide a rich network of deterministic relationships to interweave the space of hypotheses. A number of knowledge-based AI representational schemes that generalize the results of the early consultation programs have emerged recently (EMYCIN, EXPERT, AGE). They provide techniques and tools for system building that promise to be very versatile in helping to design new consultation programs.