Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53367, first published .
Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study

Andrew J McMurry   1, 2 , PhD ;   Amy R Zipursky   1, 3 , MD, MBI ;   Alon Geva   1, 4, 5 , MD, MPH ;   Karen L Olson   1, 2 , PhD ;   James R Jones   1 , MPhil ;   Vladimir Ignatov   1 , MFA ;   Timothy A Miller   1, 2 , PhD ;   Kenneth D Mandl   1, 2, 6 , MD, MPH

1 Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, United States

2 Department of Pediatrics, Harvard Medical School, Boston, MA, United States

3 Division of Pediatric Emergency Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON, Canada

4 Division of Critical Care Medicine, Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children's Hospital, Boston, MA, United States

5 Department of Anaesthesia, Harvard Medical School, Boston, MA, United States

6 Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States

Corresponding Author:

  • Kenneth D Mandl, MD, MPH
  • Computational Health Informatics Program
  • Boston Children's Hospital
  • Landmark 5506 Mail Stop BCH3187, 401 Park Drive
  • Boston, MA, 02215
  • United States
  • Phone: 1 6173554145
  • Email: kenneth_mandl@harvard.edu