A Machine Learning Approach to Identify NIH-Funded Applied Prevention Research.

Journal: American journal of preventive medicine
Published Date:

Abstract

INTRODUCTION: To fulfill its mission, the NIH Office of Disease Prevention systematically monitors NIH investments in applied prevention research. Specifically, the Office focuses on research in humans involving primary and secondary prevention, and prevention-related methods. Currently, the NIH uses the Research, Condition, and Disease Categorization system to report agency funding in prevention research. However, this system defines prevention research broadly to include primary and secondary prevention, studies on prevention methods, and basic and preclinical studies for prevention. A new methodology was needed to quantify NIH funding in applied prevention research.

Authors

  • Jennifer Villani
    Office of Disease Prevention, NIH, Rockville, Maryland. Electronic address: villani@nih.gov.
  • Sheri D Schully
    Office of Disease Prevention, NIH, Rockville, Maryland.
  • Payam Meyer
    Office of Portfolio Analysis, NIH, Bethesda, Maryland.
  • Ranell L Myles
    Office of Disease Prevention, NIH, Rockville, Maryland.
  • Jocelyn A Lee
    Office of Disease Prevention, NIH, Rockville, Maryland.
  • David M Murray
    Office of Disease Prevention, NIH, Rockville, Maryland.
  • Ashley J Vargas
    Office of Disease Prevention, NIH, Rockville, Maryland.