Kuang Zhaobin, Bao Yujia, Thomson James, Caldwell Michael, Peissig Peggy, Stewart Ron, Willett Rebecca, Page David
The University of Wisconsin, Madison, WI, USA.
The Massachusetts Institute of Technology, Cambridge, MA, USA.
Methods Mol Biol. 2019;1903:255-267. doi: 10.1007/978-1-4939-8955-3_15.
We present the baseline regularization model for computational drug repurposing using electronic health records (EHRs). In EHRs, drug prescriptions of various drugs are recorded throughout time for various patients. In the same time, numeric physical measurements (e.g., fasting blood glucose level) are also recorded. Baseline regularization uses statistical relationships between the occurrences of prescriptions of some particular drugs and the increase or the decrease in the values of some particular numeric physical measurements to identify potential repurposing opportunities.
我们提出了一种利用电子健康记录（EHR）进行计算药物再利用的基线正则化模型。在电子健康记录中，会记录不同患者在不同时间的各种药物处方。同时，也会记录数值型身体测量数据（例如空腹血糖水平）。基线正则化利用某些特定药物处方的出现与某些特定数值型身体测量数据值的增加或减少之间的统计关系，来识别潜在的药物再利用机会。
