Affiliations: [a] School of Computer Science, South China Normal University, Guangzhou, China
| [b]
The First Affiliated Hospital of Jinan University, Guangzhou, China
| [c] School of Life Sciences, South China Normal University, Guangzhou, China
| [d] Department of Computer Science and EngineeringUniversity of Chittagong, Chittagong, Bangladesh
Correspondence:
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Corresponding author. Dingju Zhu, School of Computer Science, South China Normal University, Guangzhou, China. E-mail: zhudingju@m.scnu.edu.cn.
Note: [1] Co-first author: Jun Huang, Yumin Zhuo, Xuemei Tian
Abstract: Conventional methods for disease treatment plan rely too much on the subjective experience and theoretical knowledge of doctors The uncertain decisions of doctors may lead to wrong treatment plans. This paper provides a treatment suggestion system based on big data and knowledge base. The system no longer relies on the subjective experience of doctors, but relies on the objective historical data of treatment cases including disease information, personal information, treatment plans and the treatment effects of the treatment plans. The suggested treatment plans are much more targeted and reliable, thereby assisting doctors to determine disease treatment plans more quickly, accurately and reasonably.
Keywords: Disease treatment plan, big data, knowledge base
