Translate and Summarize Complaints of Patient to Electronic Health Record by BiLSTM-CNN Attention model

Auto-generation of Electronic Health Record (EHR) is a difficult problem in intelligent medical diagnose and health care. This paper proposes a BiLSTM-CNN attention model which directly reads patientsu0027 complaints and generates EHRs. The BiLSTM-CNN attention model is a combination of BiLSTM and CNN model with attention. The attention is achieved through the Encode-Decode model. With the coded input text the BiLSTM-CNN model is trained and used to generate EHRs. The model is validated against reference EHRs which shows satisfactory result. The ROUGE is also used as the evaluation metrics to compare with other baseline models. A brief discussion about the limitations, weakness and the future work of the proposed mode are given.