Cross domains adversarial learning for Chinese named entity recognition for online medical consultation.

Deep learning methods have been applied to Chinese named entity recognition for the online medical consultation. They require a large number of marked samples. However, no such database is available at present. This paper begins with constructing a larger labelled Chinese texts database for the online medical consultation. Second, a basic framework unit is proposed, which is pre-trained by the transfer learning from both Bidirectional language model and Mask language model trained on the larger unlabelled data. Finally, cross domains adversarial learning (CDAL) for Chinese named entity recognition is proposed to further improve the performance, which not only uses the pre-trained basic framework unit, but also uses the adversarial multi-task learning on both electronic medical record texts and online medical consultation texts. Experimental results validate the effectiveness of CDAL.

[Prevention and effective treatment of opposite subdural effusion after decompressive cranium].

OBJECTIVE: To explore the prevention and effective treatment of opposite subdural effusion after decompressive cranium. METHODS: Retrospective analyses were conducted for 79 cases of opposite subdural effusion after decompressive cranium. And the efficacies of various methods were compared. RESULTS: Among them, 78 cases were cured by enswathing with elastic bondage. And one case improved through cavity fluid drainage catheter. CONCLUSION: Enswathing with elastic bondage is an effective, simple and economic method of managing opposite subdural effusion after decompressive cranium.