Baykal N, Reggia J A, Yalabik N, Erkmen A, Beksac M S
Dept. of Computer Science, University of Maryland, College Park 20742.
Proc Annu Symp Comput Appl Med Care. 1994:865-9.
Doppler umbilical artery blood flow velocity waveform measurement is used in perinatal surveillance for the evaluation of pregnancy status. There is an ongoing debate on the predictive value of Doppler measurements concerning the critical effect of the selection of parameters for the evaluation of Doppler output. In this paper, we describe how neural network methods can be used both to discover relevant classification features and subsequently to classify patients. Classification accuracy varied from 92-99% correct.
多普勒脐动脉血流速度波形测量用于围产期监测以评估妊娠状态。关于多普勒测量的预测价值，围绕用于评估多普勒输出的参数选择的关键影响存在持续的争论。在本文中，我们描述了神经网络方法如何既能用于发现相关分类特征，又能随后对患者进行分类。分类准确率在92%至99%之间。
