1. Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph
- Author
-
Ling Yin, Fulin Liu, Cong Wang, Wanheng Liu, and Zhiyu Ni
- Subjects
Medicine (General) ,Article Subject ,Computer science ,Biomedical Engineering ,Health Informatics ,Recommender system ,Machine learning ,computer.software_genre ,Health administration ,Pattern Recognition, Automated ,R5-920 ,Health care ,Medical technology ,Humans ,R855-855.5 ,Artificial neural network ,business.industry ,Models, Theoretical ,Comprehension ,Knowledge graph ,Surgery ,Artificial intelligence ,State (computer science) ,Neural Networks, Computer ,business ,computer ,Delivery of Health Care ,5G ,Biotechnology ,Research Article - 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.
- Published
- 2021