Gathering Real World Evidence with Cluster Analysis for Clinical Decision Support
Clinical decision support systems are information technology systems that assist clinical decision-making tasks,which have been shown to enhance clinical performance.Cluster analysis,which groups similar patients together,aims to separate patient cases into phenotypically heterogenous groups and defining therapeutically homogeneous patient subclasses.Useful as it is,the application of cluster analysis in clinical decision support systems is less reported.Here,we describe the usage of cluster analysis in clinical decision support systems,by first dividing patient cases into similar groups and then providing diagnosis or treatment suggestions based on the group profiles.This integration provides data for clinical decisions and compiles a wide range of clinical practices to inform the performance of individual clinicians.We also include an example usage of the system under the scenario of blood lipid management in type 2 diabetes.These efforts represent a step toward promoting patient-centered care and enabling precision medicine.
Cluster Analysis Expert Systems Software
Eryu Xia Haifeng Liu Jing Li Jing Mei Xuejun Li Enliang Xu Xiang Li Gang Hu Guotong Xie Meilin Xu
IBM Research-China,Beijing,China Department of Endocrinology and Diabetes,the First Affiliated Hospital,Xiamen University,Xiamen,Fuji Pfizer Investment Co.Ltd.,Beijing,China
国际会议
第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)
苏州
英文
1185-1189
2017-08-21（万方平台首次上网日期，不代表论文的发表时间）