Published on in Vol 10, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40039, first published .
Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study

Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study

Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study

Natasha Alexander   1 , MBBS, MSc ;   Catherine Aftandilian   2 , MD ;   Lin Lawrence Guo   3 , PhD ;   Erin Plenert   3 , MSc ;   Jose Posada   4 , PhD ;   Jason Fries   5 , PhD ;   Scott Fleming   5 , BSc ;   Alistair Johnson   3 , PhD ;   Nigam Shah   5 , MD, PhD ;   Lillian Sung   1, 3 , MD, PhD

1 Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, ON, Canada

2 Division of Hematology/Oncology, Department of Pediatrics, Stanford University, Palo Alto, CA, United States

3 Program in Child Health Evaluative Sciences, Peter Gilgan Centre for Research and Learning, Toronto, ON, Canada

4 Department of Systems Engineering and Computing, Universidad del Norte, Barranquilla, Colombia

5 Stanford Center for Biomedical Informatics Research, Department of Biomedical Data Science, Stanford University, Palo Alto, CA, United States

Corresponding Author:

  • Lillian Sung, MD, PhD
  • Division of Haematology/Oncology
  • The Hospital for Sick Children
  • 555 University Avenue
  • Toronto, ON, M5G1X8
  • Canada
  • Phone: 1 416-813-5287
  • Fax: 1 416-813-5979
  • Email: lillian.sung@sickkids.ca