A study on the use of belief functions for medical expert systems

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Abstract
This paper describes methods for extracting belief functions from data and incorporating expert opinions. The techniques are applied to a medical domain involving the diagnosis of diferent types of liver diseases. This is a domain in which experts are poor at predicting precise (singleton) outcomes. The methodology developed is shown to perform considerably better than the experts alone. Several methods by which to find belief functions from data are compared, and some methods proposed here are shown to outperform a suggestion by Shafer. The system has been fully implemented on a SEQUENT parallel machine and has a user interface which is simple to use and allows for changes and questions.