Smart Education & Healthcare: Deep learning-based Cross-Domain English data translation for Real-Time Mobile healthcare

Abstract

Internet technology and smart medical equipment have been rapidly developed and widely popularized. Telemedicine can improve the efficiency of patients' medical treatment and can facilitate patients to receive doctor's diagnosis and treatment, which saves medical resources and facilitate the monitoring of patients suffering from geriatric diseases and chronic diseases. In this work, we adopt the deep learning model to form a medical-oriented English translation mechanism, based on which we can improve diagnostic efficiency and promote the development of smart telemedicine systems. We combine the recurrent neural network and attention mechanism to design an English translation model, which can solve the language barrier in the cross-domain medical diagnosis process and improve the diagnosis efficiency. Specifically, first, we design a RNN translation model based on the encoder-decoder structure. Second, we incorporate an attention mechanism into the designed translation model to improve the translation performance of the model. The experimental results show that the proposed mechanism is efficient.