A preliminary study on imbalanced syndrome differentiation of cold and heat

Hu, Qinan; Yu, Tong; Zhu, Liling; Li, Jinghua; Yu, Qi; Gu, Yueguo

doi:10.1109/healthcom.2017.8210831

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…We also use these indicators to compare the results of the proposed model with seven preexisting classification models. ese comparisons are shown in Table 2 in which (1), ( 2), (3), ( 4), ( 5), (6), and (7) correspond to [22,23,[25][26][27][28][29], respectively, and ( 8) is the proposed method (baseline).…”

Section: Experimental Results and Analysismentioning

confidence: 99%

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BJBN： BERT-JOIN-BiLSTM Networks for Medical Auxiliary Diagnostic

Xu¹,

Yuan

Chen

2022

Journal of Healthcare Engineering

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This study proposed a medicine auxiliary diagnosis model based on neural network. The model combines a bidirectional long short-term memory（Bi-LSTM）network and bidirectional encoder representations from transformers (BERT), which can well complete the extraction of local features of Chinese medicine texts. BERT can learn the global information of the text, so use BERT to get the global representation of medical text and then use Bi-LSTM to extract local features. We conducted a large number of comparative experiments on datasets. The results show that the proposed model has significant advantages over the state-of-the-art baseline model. The accuracy of the proposed model is 0.75.

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Section: Experimental Results and Analysismentioning

confidence: 99%

“…Kale et al [ 22 ] applied a modern LSTM method to large datasets of multiple clinical time series for the first time and achieved certain results. Hu et al [ 23 ] proposed a model that can be used to assist in diagnosis by calculating the Yin and Yang dialectic based on FastText. The input to these models can be words or characters.…”

Section: Related Workmentioning

confidence: 99%