Astion M L, Wilding P
Department of Laboratory Medicine, University of Washington, Seattle 98195.
Arch Pathol Lab Med. 1992 Oct;116(10):995-1001.
Neural networks are a group of computer-based pattern recognition technologies that have been applied to problems in clinical diagnosis. This review focuses on one member of the group of neural networks, the backpropagation network. The steps in creating a backpropagation network are (1) collecting adequate training facts, (2) choosing the specific network structure, (3) training the network, and (4) cross-validating the trained network. The first published applications of backpropagation networks to problems in pathology and laboratory medicine have appeared recently. These applications are in the areas of image analysis and interpretation of laboratory results, and they demonstrate the feasibility of the approach.
神经网络是一组基于计算机的模式识别技术，已应用于临床诊断问题。本综述聚焦于神经网络组中的一个成员——反向传播网络。创建反向传播网络的步骤包括：（1）收集足够的训练数据；（2）选择特定的网络结构；（3）训练网络；（4）对训练好的网络进行交叉验证。反向传播网络在病理学和检验医学问题上的首次公开应用最近已经出现。这些应用涉及图像分析和检验结果解读领域，并且证明了该方法的可行性。
