Machine learning data sources in pediatric sleep research: assessing racial/ethnic differences in electronic health record–based clinical notes prior to model training

Machine learning data sources in pediatric sleep research: assessing racial/ethnic differences in electronic health record–based clinical notes prior to model training

IntroductionPediatric sleep problems can be detected across racial/ethnic subpopulations in primary care settings. However, the electronic health record (EHR) data documentation that describes patients' sleep problems may be inherently biased due to both historical biases and informed presence....

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Bibliographic Details
Main Authors: Mattina A. Davenport, Joseph W. Sirrianni, Deena J. Chisolm
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Sleep
Subjects:
sleep
equity
public health
primary care
informatics
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/frsle.2024.1271167/full

Internet

https://www.frontiersin.org/articles/10.3389/frsle.2024.1271167/full

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