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A new research has been conducted to improve the efficiency of biomedical text mining and computation. The research uses deep learning (DL) and natural language processing (NLP) to transform unstructured textual data into refined knowledge. Additionally, the research does not require additional training datasets, external knowledge, and complex training process. The results of the research demonstrate that the proposed model is better at mining semantic information, alleviating the problem of label inconsistency, and has higher entity recognition ability.
