Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

Journal: Journal of medical Internet research
Published Date: Aug 4, 2020

Abstract

BACKGROUND: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a specific group of patients during hospitalization, and there is limited knowledge on the baseline risk in the general population for preventing CA-AKI-associated hospitalization.

Authors

  • Chien-Ning Hsu
    School of Pharmacy, College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Chien-Liang Liu
    Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.
  • You-Lin Tain
    Division of Pediatric Nephrology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung Medical University, Kaohsiung, Taiwan.
  • Chin-Yu Kuo
    Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.
  • Yun-Chun Lin
    Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan.

Keywords

External Resources

Popular Topics
Recent Journals