Design of a self-adaptive brain tumor diagnostic system

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題名:	Design of a self-adaptive brain tumor diagnostic system
作者:	C. H. Wang;S. S. Tseng;T. P. Hong
貢獻者:	Department of Information Science and Applications
日期:	1995
上傳時間:	2009-11-30 08:03:08 (UTC+0)
出版者:	Asia University
摘要:	This paper presents a self-adaptive expert system for brain tumor diagnosis we have designed. The Brain Tumor Diagnostic System (BTDS) we propose consists of three main components: knowledge building, inference, and knowledge refinement. In the knowledge building component, an inductive learning algorithm, RASSISTANT, constructs an initial knowledge base from noisy examples, eliminating a major difficulty in developing diagnostic expert systems. In the inference component, an inference engine exploits rules in the knowledge base to help diagnosticians determine brain tumor causes according to computer tomography pictures. A simple rule refinement scheme, PCC, is also proposed to modify the existing knowledge base during inference, which dramatically improves the accuracy of the derived rules. BTDS performance has been evaluated on 270 actual brain tumor cases. Results show that BTDS can achieve an accuracy of over 98%.
關聯:	Journal of Information Science and Engineering 11(2):274-294
顯示於類別:	[行動商務與多媒體應用學系] 期刊論文

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