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J Pediatr. 2019 May;208:12-22. doi: 10.1016/j.jpeds.2018.12.041. Epub 2019 Jan 25.

Data Science for Child Health.

Author information

1
Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO; CU Data Science to Patient Value (D2V), University of Colorado School of Medicine, Aurora, CO; Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO; Adult and Child Consortium for Outcomes Research and Delivery Science (ACCORDS), University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO; Computational Bioscience Program, University of Colorado Denver Anschutz Medical Campus, Aurora, CO. Electronic address: tell.bennett@ucdenver.edu.
2
Computational Bioscience Program, University of Colorado Denver Anschutz Medical Campus, Aurora, CO.
3
Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO; Adult and Child Consortium for Outcomes Research and Delivery Science (ACCORDS), University of Colorado School of Medicine and Children's Hospital Colorado, Aurora, CO.
4
CU Data Science to Patient Value (D2V), University of Colorado School of Medicine, Aurora, CO; Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO; Computational Bioscience Program, University of Colorado Denver Anschutz Medical Campus, Aurora, CO.
5
Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, CT.
6
Pediatric Critical Care, University of Virginia School of Medicine, Charlottesville, VA.
7
Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO; Computational Bioscience Program, University of Colorado Denver Anschutz Medical Campus, Aurora, CO.

KEYWORDS:

classification; clinical; data mining; data warehousing; decision support systems; forecasting; machine learning; neural networks; phenotype

PMID:
30686480
PMCID:
PMC6486872
[Available on 2020-05-01]
DOI:
10.1016/j.jpeds.2018.12.041

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