Mulsant B H
Laval University, Quebec City.
MD Comput. 1990 Jan-Feb;7(1):25-36.
During the past decade, artificial neural networks have been established as promising psychological and computational models. The proponents of neural computing believe that it offers new solutions to problems that have been intractable so far. To study the suitability of neural networks for performing sequential diagnostic classification, I have used a network that, over time, becomes increasingly proficient at diagnosing dementia. A description of the implementation, training, and behavior of this network illustrates how neural-network technology might contribute to clinical computing.
在过去十年中,人工神经网络已成为很有前景的心理学和计算模型。神经计算的支持者认为,它为迄今难以解决的问题提供了新的解决方案。为了研究神经网络用于执行顺序诊断分类的适用性,我使用了一个随着时间推移在诊断痴呆症方面越来越熟练的网络。对该网络的实现、训练和行为的描述说明了神经网络技术如何可能有助于临床计算。