Li Y C, Haug P J, Warner H R
Department of Medical Informatics, University of Utah, Salt Lake City.
Proc Annu Symp Comput Appl Med Care. 1994:765-9.
Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains.
《伊利亚特》是一个大型医学诊断系统，涵盖2000多种诊断和9000多项检查结果。由于该系统的规模和复杂性，强大的知识表示对于一致且高效地对所涉及的医学知识进行建模至关重要。在本文中，我们描述了《伊利亚特》目前使用的知识表示以及一种基于贝叶斯网络形式主义的概率表示，后者可利用《伊利亚特》知识库中包含的信息推导得出。
