人工智能在听力学中的应用

M. Juhola, K. Viikki, J. Laurikkala, Y. Auramo, E. Kentala, I. Pyykkö
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引用次数: 2

摘要

本文将基于人工智能理论的机器学习方法应用于一些耳神经疾病的计算机辅助决策,如梅涅氏病。研究了决策树、遗传算法和神经网络三种方法。通过使用这种机器学习方法,用一组有代表性的案例训练集对决策程序进行训练,并用另一组案例进行测试。机器学习方法对我们基于模式识别方法的耳神经专家系统One也很有用。只要有足够大的训练集,这些方法能够区分所包括的六种疾病之间的大多数测试病例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of artificial intelligence in audiology
In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Me´nie`re's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.
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