Named Entity Recognition in Chinese Clinical Text Using Deep Neural ...
pubmed.ncbi.nlm.nih.gov › ...
In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering ...
In this study, we propose to investigate the use of deep neural network in NER from Chinese clinical text. We developed a deep neural network (DNN) approach for ...
A novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering approach is investigated and ...
Dec 1, 2022 · Named entity recognition in Chinese EMRs is a sequence labeling task in natural language processing. The deep learning-based method effectively ...
Clinical named entity recognition aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic ...
Dec 18, 2015 · In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal ...
Apr 28, 2020 · We propose a deep stacked neural network for Chinese clinical NER. The neural network stacks two bidirectional long-short term memory and gated recurrent unit ...
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CNER aims to identify the boundaries and types of specific medical entities from unstructured text, such as diseases, symptoms, treatments, exams, body parts ...
Dec 31, 2021 · This study presents a novel multi-task deep neural network model for Chinese NER in the medical domain.
Oct 22, 2024 · This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to ...