Prediction of vancomycin dose on high-dimensional data using machine learning techniques.

Journal: Expert review of clinical pharmacology
PMID: 33835879

Abstract

OBJECTIVES: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of individual factors and extensibility is insufficient. We aimed to develop an optimal dosing algorithm for vancomycin based on the high-dimensional data using the proposed variable engineering and machine-learning methods.

Authors

  • Xiaohui Huang
    1 Department of General Surgery, Chinese PLA General Hospital, Beijing 100853, China.
  • Ze Yu
    Beijing Medicinovo Technology Co. Ltd., Beijing, China.
  • Xin Wei
    Department of Urology, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510700, China.
  • Junfeng Shi
    Department of Nephrology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Yu Wang
    Clinical and Technical Support, Philips Healthcare, Shanghai, China.
  • Zeyuan Wang
    School of Computer Science, The University of Sydney, Australia; Real-World Study Group, Medicinovo Inc., China.
  • Jihui Chen
    Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Shuhong Bu
    Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Lixia Li
    Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Fei Gao
    College of Biological Sciences, China Agricultural University, Beijing 100193, China.
  • Jian Zhang
    College of Pharmacy, Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China.
  • Ajing Xu
    Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Keywords

External Resources

Popular Topics
Recent Journals