%0 Journal Article
%T In-depth mining of clinical data: the construction of clinical prediction model with R
%A Bo Li
%A Guo-Zhen Zhao
%A Hui-Na Zhang
%A Jing Hu
%A Kai-Rui Jin
%A Po Huang
%A Shao-Jia Wang
%A Tian-Song Zhang
%A Wei-Wei Wang
%A Xing-Xing Chen
%A Xuan-Yi Wang
%A Yan Li
%A Yi-Shan Chen
%A Zhi-Rui Zhou
%A Zi-Wei Wang
%J SCIE-indexed Journal
%D 2019
%R 10.21037/atm.2019.08.63
%X For a doctor, if there is a certain ˇ°specific functionˇ± to predict whether a patient will have some unknown outcome, then many medical practice modes or clinical decisions will change. Such demand is so strong that almost every day we will hear such a sigh ˇ°If I could know in advance, I would certainly not do this!ˇ±. For example, if we can predict that a patient with malignant tumor is resistant to a certain chemotherapy drug, then we will not choose to give the patient the drug; if we can predict that a patient may have major bleeding during surgery, then we will be careful and prepare sufficient blood products for the patient during the operation; if we can predict that a patient with hyperlipidemia will not benefit from some lipid-lowering drug, then we can avoid many meaningless medical interventions
%U http://atm.amegroups.com/article/view/29812/html