Elman神经网络与深度神经网络在轻度阿尔茨海默病诊断中的作用比较

The Neuroscience Journal of Shefaye Khatam Pub Date : 2021-12-01 DOI:10.52547/shefa.10.1.1

elias mazrooei, M. Azarnoosh, M. Ghoshuni, mohammadmehdi khalilzadeh

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引用次数: 1

摘要

结论:在提出的对健康、轻症、重症患者三类患者进行分类的处理方法中，脑信号特征与医学图像相结合的方法提高了CNN和Elman分类器结果的准确率。

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Comparison of the Function of the Elman Neural Network and the Deep Neural Network for the Diagnosis of Mild Alzheimer's Disease

Conclusion: Among the processing methods proposed to classify the three classes of healthy, mild patient and severe patient, the method of combining brain signal characteristics and medical images has increased the accuracy of CNN and Elman classifier results.

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The Neuroscience Journal of Shefaye Khatam

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