Journal
Global Pediatrics
Publication Date
9-1-2024
Volume
9
First Page
100220
Document Type
Open Access Publication
DOI
10.1016/j.gpeds.2024.100220
Rights and Permissions
Seamon E, Mattera JA, Keim SA, Leerkes EM, Rennels JL, Kayl AJ, Kulhanek KM, Narvaez D, Sanborn SM, Grandits JB, Schetter CD, Coussons-Read M, Tarullo AR, Schoppe-Sullivan SJ, Thomason ME, Braungart-Rieker JM, Lumeng JC, Lenze SN, Christian LM, Saxbe DE, Stroud LR, Rodriguez CM, Anzman-Frasca S, Gartstein MA. Leveraging machine learning to study how temperament scores predict pre-term birth status. Glob Pediatr. 2024 Sep;9:100220. doi: 10.1016/j.gpeds.2024.100220. © 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/bync/4.0/).
Recommended Citation
Seamon, Erich; Lenze, Shannon N; and et al., "Leveraging machine learning to study how temperament scores predict pre-term birth status." Global Pediatrics. 9, 100220 (2024).
https://digitalcommons.wustl.edu/oa_4/6419
Department
ICTS (Institute of Clinical and Translational Sciences)
Additional Links
Supplemental material is available for this article at publisher site.
