May 23, 2023 · This paper proposes a new model that combines the BERT pretraining model and the BilSTM-CRF model. First, word embedding with semantic information is obtained.
This paper proposes a new model that combines the BERT pre-training model and the BiConvLSTM-CRF model, namely BERT-BiLSTM-CRF.
May 10, 2023 · A Hybrid Model Based on Deep Convolutional Network for Medical Named Entity Recognition. Wiley. Journal of Electrical and Computer Engineering.
Jan 1, 2023 · The typical pretrained model's feature extraction capabilities are insufficient for medical named entity identification, ...
The main purpose of NER is to identify and classify specific entity from medical records, such as side symptoms, drugs and treatment, this task is usually ...
Artificial Neural Network · Convolution. Conference Paper. A hybrid model based on deep convolutional neural network for medical named entity recognition.
Mar 7, 2022 · This paper proposes a hybrid neural network medical text named entity recognition model. First, a coding method based on a fully self ...
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Named Entity Recognition of Medical Text Based on the Deep Neural ...
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A hybrid neural network medical text named entity recognition model that uses two-dimensional convolutional decoding to associate the current position word ...
Hybrid neural network model based on medical MC-BERT. Named entity recognition in Chinese EMRs is a sequence labeling task in natural language processing. The ...
Jun 7, 2021 · We propose a hybrid deep learning approach to improve the recognition accuracy of NER. Specifically, our approach applies the Bidirectional Encoder ...