Document-aware Information Extractor for Chinese Medical Dialogue
Yifei He, Yan Li, Senbao Hou · 2021
Electronic medical records (EMRs) are one of the methods to help doctors effectively manage and analyze patient medical records. These EMRs not only help doctors save a lot of time to analyze medical records, but also reduce the hospital's demand for doctors and reduce hospital expenditure costs. Therefore, we proposed the document-aware information extractor (DIE) to effectively extract the information about the patient's physical condition in the conversation between the doctor and the patient. In this paper, we proposed a encoder-decoder model to extract the medical items amongst the doctor-patient dialogue for further usage of EMRs generation. The experimental result shows that our model achieves better results compared to the baseline models, which indicates the model effectiveness.