This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2206) Developmental Problems (39) Artificial Intelligence (1194) Machine Learning (1383)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51996, first published .
Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks–Based Deep Learning: Development and Validation Study

Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks–Based Deep Learning: Development and Validation Study

Comprehensive Assessment and Early Prediction of Gross Motor Performance in Toddlers With Graph Convolutional Networks–Based Deep Learning: Development and Validation Study

Authors of this article:

Sulim Chun1 Author Orcid Image ;   Sooyoung Jang1 Author Orcid Image ;   Jin Yong Kim1 Author Orcid Image ;   Chanyoung Ko1 Author Orcid Image ;   JooHyun Lee1 Author Orcid Image ;   JaeSeong Hong1 Author Orcid Image ;   Yu Rang Park1 Author Orcid Image
Article Authors Cited by Tweetations (2) Metrics

Sulim Chun   1 * , BA ;   Sooyoung Jang   1 * , MD ;   Jin Yong Kim   1 , MS ;   Chanyoung Ko   1 , MD ;   JooHyun Lee   1 , BSN ;   JaeSeong Hong   1 , BBA ;   Yu Rang Park   1 , PhD

1 Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Yu Rang Park, PhD
  • Department of Biomedical Systems Informatics
  • Yonsei University College of Medicine
  • 6th floor
  • 50-1 Yonsei-ro, Seodaemun-gu
  • Seoul, 03722
  • Republic of Korea
  • Phone: 82 2-2228-2493
  • Email: yurangpark@yuhs.ac