计算机科学
编码(社会科学)
人工神经网络
ICD-10号
人工智能
数据科学
深层神经网络
医学分类
深度学习
线性网络编码
机器学习
数据挖掘
计算机安全
医学
数学
网络数据包
护理部
精神科
统计
作者
Fei Teng,Yiming Liu,Tianrui Li,Yi Zhang,Shuangqing Li,Yue Zhao
出处
期刊:IEEE Transactions on Knowledge and Data Engineering
[Institute of Electrical and Electronics Engineers]
日期:2022-01-01
卷期号:: 1-1
被引量:21
标识
DOI:10.1109/tkde.2022.3148267
摘要
The International Classification of Diseases (ICD) is a standard for categorizing physical conditions, which has been widely used for analyzing clinical data and monitoring health issues. Manual ICD coding takes a long time and is vulnerable to errors, so people pay more and more attention to the application of deep neural networks in ICD automatic coding. However, there is still no comprehensive review of these studies and prospects for further research. This paper is not limited to the study of deep neural networks, but gives a formal definition of ICD coding problems, and then systematically reviews the existing literature on how to design deep neural networks to address the four major challenges of ICD coding tasks. This paper also summarizes the public data sets and future research directions, to provide a guidance for the research of ICD coding in medical field.
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