A machine learning-based screening tool for genetic syndromes in children - Authors' reply

Authors

Antonio R. Porras, Department of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA. Electronic address: antonio.porras@cuanschutz.edu.
Kenneth Rosenbaum, Rare Disease Institute, Department of Genetics and Metabolism, Children's National Hospital, Washington, DC, USA.
Carlos Tor-Diez, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
Marshall Summar, Rare Disease Institute, Department of Genetics and Metabolism, Children's National Hospital, Washington, DC, USA.
Marius George Linguraru, Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA; Department of Biomedical Engineering, School of Engineering and Applied Science, George Washington University, Washington, DC, USA; Department of Pediatrics and Department of Radiology, School of Medicine and Health Sciences, George Washington University, Washington, DC, USA.

Document Type

Journal Article

Publication Date

5-1-2022

Journal

The Lancet. Digital health

Volume

4

Issue

5

DOI

10.1016/S2589-7500(22)00047-4

APA Citation

Porras, Antonio R.; Rosenbaum, Kenneth; Tor-Diez, Carlos; Summar, Marshall; and Linguraru, Marius George, "A machine learning-based screening tool for genetic syndromes in children - Authors' reply" (2022). GW Authored Works. Paper 1039.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/1039

Department

Pediatrics