Analysis and forecast of clinical decision support system for diabetes mellitus based on big data technique
10.3760/cma.j.issn.1673-4181.2017.03.015
- VernacularTitle:基于大数据技术的糖尿病临床决策支持系统分析与展望
- Author:
Jiarui SI
;
Dehu MU
;
Li SUN
;
Zhen QIAO
;
Kun YANG
- Keywords:
Diabetes mellitus;
Big data technology;
Clinical decision support system
- From:
International Journal of Biomedical Engineering
2017;40(3):216-220,后插4
- CountryChina
- Language:Chinese
-
Abstract:
Diabetes is a chronic noncommunicable disease,which is can't be cured,and only can be suppressed by long-term treatment and self-management.The clinical decision support system can simulate the thinking process of diabetes specialists in disease diagnosis,and can provide the regular medical treatment plans and recommend the optimal plans to doctors.Most of the existing clinical decision support systems are based on clinical guidelines,rule-based and case-based reasoning as well as ontology-based systems.The big data technology can acquire and process multiple heterogeneous data,and provide a more scientific personalized treatment plan.In recent years,a variety of big date processing methods have been applied to the clinical diagnosis of diabetes based on decision tree,neural network,fuzzy logic,support vector machine,APRIORI association rules and multidimensional analysis,and timing mining.However,these methods are still in preliminary stage.The framework of diabetes clinical decision support system based on big data technology was analyzed,and the future diagnostic and treatment methods were forecast.
