Medical Text Classification using Convolutional Neural Networks

TL;DR

This paper introduces a deep convolutional neural network approach for classifying clinical text at the sentence level, demonstrating significant performance improvements over existing NLP methods.

Contribution

It presents a novel application of CNNs to clinical text classification, achieving about 15% better accuracy than traditional approaches.

Findings

CNN-based model outperforms existing methods by 15%

Effective for broad categorization of health information

Demonstrates robustness on clinical text datasets

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%.