SELF-INTEGRATING KNOWLEDGE-BASED BRAIN-TUMOR DIAGNOSTIC SYSTEM

In this paper we present a self-integrating knowledge-based expert sys tem for brain tumor diagnosis. The system we propose comprises knowled ge building, knowledge inference and knowledge refinement. During know ledge building, an automatic knowledge-integration process, based on D arwin's theory of natural selection, integrates knowledge derived from knowledge-acquisition tools and machine-learning methods to construct an initial knowledge base, thus eliminating a major bottleneck in dev eloping a brain tumor diagnostic system. During the knowledge inferenc e process, art inference engine exploits rules in the knowledge base t o help diagnosticians determine brain tumor etiologies according to co mputer tomography pictures. And, a simple knowledge refinement method is proposed to modify the existing knowledge base during inference, wh ich dramatically improves the accuracy of the derived rules. The perfo rmance of the brain tumor diagnostic system has been evaluated on actu al brain tumor cases. Copyright (C) 1996 Elsevier Science Ltd