Construction of Communication Strategies Based on Natural Language Processing in the Discourse Model of Doctor-Patient Interaction

This paper defines doctor-patient interaction from the perspectives of interaction form and maintenance of patients' health respectively, and also constructs a doctor-patient interaction discourse model.Based on the data mining technology to obtain the research data, the acquired data are preprocessed and stored in the form of dataset.Bi-LSTM is used to extract topic sentence features from the dataset, and the unsupervised pattern is transformed into a self-supervised pattern through the training and learning of auxiliary tasks to complete the construction of the discourse model of doctor-patient interaction based on topic structure.Combined with the processing flow of natural language processing and semantic technology, the communication strategy generation system for doctor-patient interaction discourse is designed, and finally the communication strategy based on natural language technology is researched and analyzed.There are significant differences between the experimental group and the control group in terms of expression ability and cognitive level (P<0.05),which concludes that compared with the traditional discourse model, the doctor-patient interactive discourse model has a higher priority, and it can effectively improve the expression ability and cognitive level of the patients' medical terminology.On the CMedQA2.0 dataset, the average performance of this paper's model is improved by 46.34% compared with the baseline model GPT-2, indicating that this paper's model has excellent performance.Under the condition of Chinese participle and topic extraction fusion, the average accuracy of this paper's system is as high as 85.02%, which indicates that the system can provide doctors with precise communication strategies based on patients' medical-related information, thereby effectively enhancing the discourse communication skills in doctor-patient interactions.