Medical Text Classification Using Convolutional Neural Networks
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health information. Through a detailed evaluation, we demonstrate t...
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Published in | Studies in health technology and informatics Vol. 235; p. 246 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
2017
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Subjects | |
Online Access | Get more information |
ISSN | 0926-9630 |
DOI | 10.3233/978-1-61499-753-5-246 |
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Abstract | We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health information. Through a detailed evaluation, we demonstrate that our method outperforms several approaches widely used in natural language processing tasks by about 15%. |
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AbstractList | We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health information. Through a detailed evaluation, we demonstrate that our method outperforms several approaches widely used in natural language processing tasks by about 15%. |
Author | Hughes, Mark Li, Irene Kotoulas, Spyros Suzumura, Toyotaro |
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Keywords | semantic clinical classification Clinical text convolutional neural network sentence classification |
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Title | Medical Text Classification Using Convolutional Neural Networks |
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