自动编码器对降低皮肤病学数据集维数的影响

2016 Medical Technologies National Congress (TIPTEKNO) Pub Date : 2016-10-01 DOI:10.1109/TIPTEKNO.2016.7863101

Abdullah Çalıskan, H. Badem, A. Basturk, M. E. Yuksel

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引用次数: 3

摘要

研究了使用自编码器对医疗数据集进行降维的效果。针对流行的皮肤病诊断基准医疗数据集，训练了两个自编码器的堆栈。采用主成分分析法对该方法进行了改进。结果表明，使用自编码器可显著提高皮肤病诊断的准确性。

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The effect of autoencoders over reducing the dimensionality of a dermatology data set

The effect of using autoencoders for dimensionality reduction of a medical data set is investigated. A stack of two autoencoders has been trained for popular benchmark medical data set for dermatological disease diagnosis. The improvement of the presented approach has been visualized by the Principal Component Analysis method. Results shows that the use of a autoencoders significantly improves the accuracy of dermatological disease diagnosis.

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2016 Medical Technologies National Congress (TIPTEKNO)

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