Methodology minute: a machine learning primer for infection prevention and control.

Journal: American journal of infection control
Published Date:

Abstract

The use of machine-learning and predictive modeling in infection prevention and control activities is increasing dramatically. In order for infection preventionists to make informed decisions on the performance of any particular model as well as to determine if the output of the model will be useful for their program needs, a suitable understanding of the creation and evaluation of these models is necessary. The purpose of this primer is to introduce the infection preventionist to the most commonly used machine-learning method in infection prevention: supervised learning.

Authors

  • Timothy L Wiemken
    Center for Health Outcomes Research, Saint Louis University, Saint Louis, Missouri 63104, USA; email: timothy.wiemken@health.slu.edu.
  • Ana Santos Rutschman
    Saint Louis University, Advanced Health Data (AHeaD) Research Institute, Center for Systems Infection Prevention, St. Louis, MO; Saint Louis University, Health Innovation and Legal Preparedness Partnership, St. Louis, MO; Saint Louis University, School of Law, Center for Health Law Studies, St. Louis, MO.