id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_2eewznxmxbgbfbsg2ousndspha	Ching-Hung Wang	Self-integrating knowledge-based brain tumor diagnostic system	1996	10	.pdf	application/pdf	5901	762	64	Self-Integrating Knowledge-Based Brain Tumor Diagnostic Abstract--In this paper, we present a self-integrating knowledge-based expert system f o r brain tumor During knowlege building, an automatic knowledge-integration process, based on Darwin's theory o f natural selection, integrates knowledge derived from knowledge-acquisition tools and machinelearning methods to construct an initial knowledge base, thus eliminating a major bottleneck in engine exploits rules in the knowledge base to help diagnosticians determine brain tumor etiologies records, to construct a complete, consistent and unambiguous knowledge base (Baral, 1991; Gragun, 1987). the machine-learning module or the knowlege-acquisition module to build a prototype knowledge base. and objective knowledge base for brain tumor diagnosis, integrated brain-tumor diagnostic knowledge base from Since rule sets generated from different knowledge knowledge base for brain tumor diagnosis. rule 1: I F Appearance_of_Enhancement = "Homogeneous" and Location = "Brain Parenchyma, temporal" T H E N Pathology is knowledge-based brain tumor diagnostic system.	./cache/work_2eewznxmxbgbfbsg2ousndspha.pdf	./txt/work_2eewznxmxbgbfbsg2ousndspha.txt