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Analysis and forecast of clinical decision support system for diabetes mellitus based on big data technique / 国际生物医学工程杂志
International Journal of Biomedical Engineering ; (6): 216-220,后插4, 2017.
Article Dans Chinois | WPRIM | ID: wpr-617962
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.

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Guide de pratique / Étude pronostique langue: Chinois Texte intégral: International Journal of Biomedical Engineering Année: 2017 Type: Article

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Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Guide de pratique / Étude pronostique langue: Chinois Texte intégral: International Journal of Biomedical Engineering Année: 2017 Type: Article