神经计算在泌尿外科:一个方向。

C. Niederberger
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引用次数: 6

摘要

神经计算是一个数学模型来源于基于生物神经元生理功能的算法的领域。这篇文章作为《分子泌尿学》后续文章的介绍,描述了神经计算建模在泌尿学领域的实际应用。在这篇介绍性的文章中,讨论了计算机技术的历史和神经计算的基础。本文回顾了确定计算模型准确性的方法,并提出了一种评估单个输入特征对模型输出的重要性的统计方法,该过程称为“特征提取”。对于那些有兴趣将该技术应用于自己的数据集的读者,引用了提供免费和商业神经计算程序的资源,并包括对作者的神经计算编程环境的简要描述。最后,讨论了通过互联网和各种计算机平台部署计算模型。
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Neural computation in urology: an orientation.
Neural computation is a field in which mathematical models are derived from algorithms based loosely on the physiological function of the biological neuron. This paper serves as an introduction to those that follow in this issue of Molecular Urology, which describe actual applications of neural computational modeling in the urologic domain. In this introductory paper, the history of computer technology and the foundations of neural computation are discussed. Methods of determining the accuracy of computation models are reviewed, and a statistical method of evaluating the significance of individual input features to the model's output, a process known as "feature extraction," is presented. Resources that provide free and commercial neural computational programs are cited for those readers interested in applying this technology to their own datasets, and a brief description of the author's neural computational programming environment is included. Finally, deployment of computational models via the Internet and various computer platforms is discussed.
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Farewell and Thank You Neural computation in urology: an orientation. Genetic adaptive neural network to predict biochemical failure after radical prostatectomy: a multi-institutional study. Predictive modeling techniques in prostate cancer. Application of Cre-loxP system to the urinary tract and cancer gene therapy.
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