Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45041, first published .
Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study

Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study

Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study

Sarah Soyeon Oh   1, 2 , PhD ;   Irene Kuang   3 , PhD ;   Hyewon Jeong   3 , MD ;   Jin-Yeop Song   4 , BSc ;   Boyu Ren   5 , PhD ;   Jong Youn Moon   6 , MD, PhD ;   Eun-Cheol Park   2 , MD, PhD ;   Ichiro Kawachi   1 , MBChB, PhD

1 Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, United States

2 Institute of Health Services Research, Yonsei University College of Medicine, Seoul, Republic of Korea

3 Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States

4 Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, United States

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

6 Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea

Corresponding Author:

  • Jong Youn Moon, MD, PhD
  • Artificial Intelligence and Big-Data Convergence Center
  • Gil Medical Center
  • Gachon University College of Medicine
  • 191 Hambangmoe-ro, Yeonsu-gu
  • Incheon, 21936
  • Republic of Korea
  • Phone: 82 1021245754
  • Email: moonjy@gachon.ac.kr