Published on in Vol 16 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50201, first published .
Applying Machine Learning Techniques to Implementation Science

Applying Machine Learning Techniques to Implementation Science

Applying Machine Learning Techniques to Implementation Science

Nathalie Huguet   1, 2 * , PhD ;   Jinying Chen   3, 4, 5 * , PhD ;   Ravi B Parikh   6 * , MPP, MD ;   Miguel Marino   1, 2 * , PhD ;   Susan A Flocke   1, 2 * , PhD ;   Sonja Likumahuwa-Ackman   1, 2 * , MID, MPH ;   Justin Bekelman   6, 7 * , MD ;   Jennifer E DeVoe   1, 2 * , MD, DPhil

1 Department of Family Medicine, Oregon Health & Science University, Portland, OR, United States

2 BRIDGE-C2 Implementation Science Center for Cancer Control, Oregon Health & Science University, Portland, OR, United States

3 Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States

4 Data Science Core, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States

5 iDAPT Implementation Science Center for Cancer Control, Wake Forest School of Medicine, Winston-Salem, NC, United States

6 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

7 Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, United States

*all authors contributed equally

Corresponding Author:

  • Nathalie Huguet, PhD
  • Department of Family Medicine
  • Oregon Health & Science University
  • 3181 SW Sam Jackson Park Road
  • Portland, OR, 97239
  • United States
  • Phone: 1 503 494 4404
  • Email: huguetn@ohsu.edu