整合概率和基于规则的系统用于临床鉴别诊断

K. Henson-Mack, H.C. Chen, D.C. Wester
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引用次数: 7

摘要

CLAUDE是一种混合的鉴别诊断专家系统,它结合了基于规则和概率的系统,将他们的独立意见与神经网络相结合。克劳德的应用是通过分析一个病人的病史来对17个中央听觉诊断区进行分类。研究了两种网络结构,其中一种只连接应用于诊断区域内同一类的节点,另一种完全连接。CLAUDE的表现比基于规则的系统或概率系统都要好得多,并且在两种系统都无法提供诊断时做出了正确的判断。此外,即使在存在不完整数据的情况下,它也能够正确分类75%。因此,使用不同标准并由神经网络平衡的两个独立系统比单独的概率系统或基于规则的系统提供更准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating probabilistic and rule-based systems for clinical differential diagnosis
CLAUDE is a hybrid expert system for differential diagnosis that combines a rule-based and probabilistic system, integrating their independent opinions with a neural network. CLAUDE's application was to classify 17 central auditory diagnostic areas by analyzing a client's case history. Two network structures were examined, one connecting only those nodes applying to the same class within a diagnostic area, and the other fully connected. CLAUDE performed much better than either a rule-based system or a probabilistic system and made correct judgments when neither system could provide a diagnosis. Furthermore, it was able to classify 75% correctly, even in the presence of incomplete data. Thus, two individual systems using different criteria and balanced by a neural network provided more accurate results than either a probabilistic or a rule-based system alone.<>
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