Abstract
In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical resources and provide treatment programs. The technique we applied is referred to as KG-based recommendation system. When several experiments have been carried out, it is demonstrated that it is more intelligent and precise in disease prediction and treatment recommendation, similar to the state of the art. Also, it works well in the accuracy and comprehension, which is much higher and highly consistent with the predictions of the theoretical model. The fact that our work involves studies of multitask healthcare management recommendation system, which can contribute to the smart healthcare development, proves to be promising and encouraging.
Highlights
Intelligent healthcare recommendation system has become a hot topic in healthcare management application research
Driven by the need for healthcare management application, an accurate and efficient healthcare recommendation system which can be applied in terminal device is playing an important role in healthcare, which can make a more comprehensive and continuous record and analysis of our health condition and can recommend appropriate health interventions and treatment programs
In order to overcome the limitations and the problems above, a novel multitask healthcare management recommendation system leveraging the knowledge graph and deep neural network based on 5G network applied in mobile and terminal device is presented in this paper
Summary
Intelligent healthcare recommendation system has become a hot topic in healthcare management application research. In order to overcome the limitations and the problems above, a novel multitask healthcare management recommendation system leveraging the knowledge graph and deep neural network based on 5G network applied in mobile and terminal device is presented in this paper. It can be applied in mobile and terminal device, which is connected to various places, such as hospitals, communities, and homes to integrate users’ health information data from multiple channels. Taking viral pneumonia as an example, when the user passes their data through our system, it will automatically rank the severity of the disease and advise the user on what grade of hospital they should go to and provide other treatment recommendations and so on
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